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2018

  1. Francesca Stival, Stefano Michieletto, Andrea De Agnoi and Enrico Pagello. Toward a better robotic hand prosthesis control: using EMG and IMU features for a subject independent multi joint regression model. In 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob). 2018. BibTeX

    @inproceedings{Stival2018,
    	abstract = "The interest on wearable prosthetic devices has boost the research for a robust framework to help injured subjects to regain their lost functionality. A great number of solutions exploit physiological human signals, such as Electromyography (EMG), to naturally control the prosthesis, reproducing what happens in the human limbs. In this paper, we propose for the first time a way to integrate EMG signals with Inertial Measurement Unit (IMU) information, as a way to improve subject-independent models for controlling robotic hands. EMG data are very sensitive to both physical and physiological variations, and this is particularly true between different subjects. The introduction of IMUs aims at enriching the subject-independent model, making it more robust with information not strictly dependent from the physiological characteristics of the subject. We compare three different models: the first based on EMG solely, the second merging data from EMG and the 2 best IMUs available, and the third using EMG and IMUs information corresponding to the same 3 electrodes. The three techniques are tested on two different movements executed by 35 healthy subjects, by using a leave-one-out approach. The framework is able to estimate online the bending angles of the joints involved in the motion, obtaining an accuracy up to 0.8634. The resulting joint angles are used to actuate a robotic hand in a simulated environment.",
    	author = "Stival, Francesca and Michieletto, Stefano and {De Agnoi}, Andrea and Pagello, Enrico",
    	booktitle = "7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)",
    	isbn = 9781538681824,
    	title = "{Toward a better robotic hand prosthesis control: using EMG and IMU features for a subject independent multi joint regression model}",
    	year = 2018
    }
    
  2. Francesca Stival, Stefano Michieletto and Enrico Pagello. Subject Independent EMG Analysis by using Low-Cost hardware. In Systems, Man, and Cybernetics (SMC), 2018 IEEE International Conference on. 2018. BibTeX

    @inproceedings{stival2018subject,
    	author = "Stival, Francesca and Michieletto, Stefano and Pagello, Enrico",
    	booktitle = "Systems, Man, and Cybernetics (SMC), 2018 IEEE International Conference on",
    	organization = "IEEE",
    	title = "Subject Independent EMG Analysis by using Low-Cost hardware",
    	year = 2018
    }
    
  3. Francesca Stival, Stefano Michieletto, Enrico Pagello, Henning Müller and Manfredo Atzori. Quantitative Hierarchical Representation and Comparison of Hand Grasps from Electromyography and Kinematic Data. In in Workshop Proceedings of the 15th International Conference on Autonomous Systems IAS-15, Workshop on Learning Applications for Intelligent Autonomous Robots (LAIAR-2018). 2018. BibTeX

    @inproceedings{stival2018quantitative,
    	author = {Stival, Francesca and Michieletto, Stefano and Pagello, Enrico and M{\"{u}}ller, Henning and Atzori, Manfredo},
    	booktitle = "in Workshop Proceedings of the 15th International Conference on Autonomous Systems IAS-15, Workshop on Learning Applications for Intelligent Autonomous Robots (LAIAR-2018)",
    	organization = "ISBN: 978-3-00-059946-0",
    	title = "Quantitative Hierarchical Representation and Comparison of Hand Grasps from Electromyography and Kinematic Data",
    	year = 2018
    }
    
  4. Francesca Stival, Michele Moro and Enrico Pagello. A first approach to a taxonomy-based classification framework for hand grasps. , 2018. BibTeX

    @article{stival2018first,
    	title = "A first approach to a taxonomy-based classification framework for hand grasps",
    	author = "Stival, Francesca and Moro, Michele and Pagello, Enrico",
    	year = 2018
    }
    
  5. Mattia Guidolin, Marco Carraro, Stefano Ghidoni and Emanuele Menegatti. A Limb-based Approach for Body Pose Recognition Using a Predefined Set of Poses. In Workshop Proceedings of the 15th International Conference on Autonomous Systems IAS-15. 2018. BibTeX

    @inproceedings{guidolin2018limb,
    	title = "A Limb-based Approach for Body Pose Recognition Using a Predefined Set of Poses",
    	author = "Guidolin, Mattia and Carraro, Marco and Ghidoni, Stefano and Menegatti, Emanuele",
    	booktitle = "Workshop Proceedings of the 15th International Conference on Autonomous Systems IAS-15",
    	year = 2018
    }
    
  6. Stefano Tortora, Stefano Michieletto and Emanuele Menegatti. Synergy-based Gaussian Mixture Model to anticipate reaching direction identification for robotic applications. In Proc. of the IAS-15 Workshop on Learning Applications for Intelligent Autonomous Robots (LAIAR-2018). 2018, 13. BibTeX

    @inproceedings{Tortora2018,
    	author = "Tortora, Stefano and Michieletto, Stefano and Menegatti, Emanuele",
    	booktitle = "Proc. of the IAS-15 Workshop on Learning Applications for Intelligent Autonomous Robots (LAIAR-2018)",
    	pages = 13,
    	title = "{Synergy-based Gaussian Mixture Model to anticipate reaching direction identification for robotic applications}",
    	year = 2018
    }
    
  7. Stefano Tortora, Stefano Michieletto and Emanuele Menegatti. Synergy-based Classification to Anticipate Reaching Direction Identification in Stroke subject for Robotic Arm Teleoperation. In SCHOOL AND SYMPOSIUM ON ADVANCED NEUROREHABILITATION (SSNR2018). 2018, 36. BibTeX

    @inproceedings{tortorasynergy,
    	title = "Synergy-based Classification to Anticipate Reaching Direction Identification in Stroke subject for Robotic Arm Teleoperation",
    	author = "Tortora, Stefano and Michieletto, Stefano and Menegatti, Emanuele",
    	booktitle = "SCHOOL AND SYMPOSIUM ON ADVANCED NEUROREHABILITATION (SSNR2018)",
    	pages = 36,
    	year = 2018
    }
    
  8. Stefano Michieletto, Francesca Stival, Francesco Castelli and Enrico Pagello. Automated and Flexible Coil Winding Robotic Framework. In ISR 2018; 50th International Symposium on Robotics. 2016, 1–4. BibTeX

    @inproceedings{michieletto2016automated,
    	title = "Automated and Flexible Coil Winding Robotic Framework",
    	author = "Michieletto, Stefano and Stival, Francesca and Castelli, Francesco and Pagello, Enrico",
    	booktitle = "ISR 2018; 50th International Symposium on Robotics",
    	pages = "1--4",
    	year = 2016,
    	organization = "VDE"
    }
    


2017

  1. Francesco Castelli, Stefano Michieletto, Stefano Ghidoni and Enrico Pagello. A machine learning-based visual servoing approach for fast robot control in industrial setting. International Journal of Advanced Robotic Systems 14(6), 2017. DOI BibTeX

    @article{Castelli2017,
    	abstract = "Industry 4.0 aims to make collaborative robotics accessible and effective inside factories. Human–robot interaction is enhanced by means of advanced perception systems which allow a flexible and reliable production. We are one of the contenders of a challenge with the intent of improve cooperation in industry. Within this competition, we developed a novel visual servoing system, based on a machine learning technique, for the automation of the winding of copper wire during the production of electric motors. Image-based visual servoing systems are often limited by the speed of the image processing module that runs at a frequency on the order of magnitude lower with respect to the robot control speed. In this article, a solution to this problem is proposed: the visual servoing function is synthesized using the Gaussian mixture model (GMM) machine learning system, which guarantees an extremely fast response. Issues related to data size reduction and collection of the data set needed to properly train the learner are discussed, and the performance of the proposed method is compared against the standard visual servoing algorithm used for training the GMM. The system has been developed and tested for a path following application on an aluminium bar to simulate the real stator teeth of a generic electric motor. Experimental results demonstrate that the proposed method is able to reproduce the visual servoing function with a minimal error while guaranteeing extremely high working frequency.",
    	author = "Castelli, Francesco and Michieletto, Stefano and Ghidoni, Stefano and Pagello, Enrico",
    	doi = "10.1177/1729881417738884",
    	issn = 17298814,
    	journal = "International Journal of Advanced Robotic Systems",
    	keywords = "Gaussian mixture model,Visual learning,computer vision,learning and adaptive systems,robot programming by demonstration,sensor-based control,visual control of robotic systems,visual servoing",
    	number = 6,
    	title = "{A machine learning-based visual servoing approach for fast robot control in industrial setting}",
    	volume = 14,
    	year = 2017
    }
    
  2. Francesca Stival, Stefano Michieletto and Enrico Pagello. How to Deploy a Wire with a Robotic Platform: Learning from Human Visual Demonstrations. Procedia Manufacturing 11:224–232, 2017. DOI BibTeX

    @article{Stival2017,
    	abstract = "In this paper, we address the problem of deploying a wire along a specific path selected by an unskilled user. The robot has to learn the selected path and pass a wire through the peg table by using the same tool. The main contribution regards the hybrid use of Cartesian positions provided by a learning procedure and joint positions obtained by inverse kinematics and motion planning. Some constraints are introduced to deal with non-rigid material without breaks or knots. We took into account a series of metrics to evaluate the robot learning capabilities, all of them over performed the targets.",
    	author = "Stival, Francesca and Michieletto, Stefano and Pagello, Enrico",
    	doi = "10.1016/j.promfg.2017.07.230",
    	issn = 23519789,
    	journal = "Procedia Manufacturing",
    	keywords = "Industry 4.0,Inverse Kinematics,Manipulators,Programming by demonstration,Robot learning",
    	pages = "224--232",
    	title = "{How to Deploy a Wire with a Robotic Platform: Learning from Human Visual Demonstrations}",
    	volume = 11,
    	year = 2017
    }
    
  3. Morris Antonello, Andrea Gobbi, Stefano Michieletto, Stefano Ghidoni and Emanuele Menegatti. A fully automatic hand-eye calibration system. In 2017 European Conference on Mobile Robots, ECMR 2017. 2017. DOI BibTeX

    @inproceedings{Antonello2017,
    	author = "Antonello, Morris and Gobbi, Andrea and Michieletto, Stefano and Ghidoni, Stefano and Menegatti, Emanuele",
    	booktitle = "2017 European Conference on Mobile Robots, ECMR 2017",
    	doi = "10.1109/ECMR.2017.8098681",
    	isbn = 9781538610961,
    	title = "{A fully automatic hand-eye calibration system}",
    	year = 2017
    }
    
  4. Francesca Stival, Stefano Michieletto and Enrico Pagello. How to Deploy a Wire with a Robotic Platform: Learning from Human Visual Demonstrations. Procedia Manufacturing 11:224 - 232, 2017. 27th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM2017, 27-30 June 2017, Modena, Italy. URL, DOI BibTeX

    @article{stival2017how,
    	title = "How to Deploy a Wire with a Robotic Platform: Learning from Human Visual Demonstrations",
    	journal = "Procedia Manufacturing",
    	volume = 11,
    	pages = "224 - 232",
    	year = 2017,
    	note = "27th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM2017, 27-30 June 2017, Modena, Italy",
    	issn = "2351-9789",
    	doi = "https://doi.org/10.1016/j.promfg.2017.07.230",
    	url = "http://www.sciencedirect.com/science/article/pii/S2351978917304389",
    	author = "Stival, Francesca and Michieletto, Stefano and Pagello, Enrico",
    	keywords = "Robot learning, Industry 4.0, Manipulators, Inverse Kinematics, Programming by demonstration"
    }
    
  5. Stefano Michieletto, Francesca Stival, Francesco Castelli, Mony Khosravi, Alberto Landini, Stefano Ellero, Roberto Landò, Nicolò Boscolo, Stefano Tonello, Bogdan Varaticeanu, Paul Minciunescu and Enrico Pagello. Flexicoil: Flexible robotized coils winding for electric machines manufacturing industry. In ICRA workshop on Industry of the future: Collaborative, Connected, Cognitive. 2017. BibTeX

    @inproceedings{michieletto2017flexicoil,
    	title = "Flexicoil: Flexible robotized coils winding for electric machines manufacturing industry",
    	author = "Michieletto, Stefano and Stival, Francesca and Castelli, Francesco and Khosravi, Mony and Landini, Alberto and Ellero, Stefano and Landò, Roberto and Boscolo, Nicolò and Tonello, Stefano and Varaticeanu, Bogdan and Minciunescu, Paul and Pagello, Enrico",
    	booktitle = "ICRA workshop on Industry of the future: Collaborative, Connected, Cognitive",
    	year = 2017
    }
    
  6. Fabian Just, Özhan Özen, Stefano Tortora, Robert Riener and Georg Rauter. Feedforward model based arm weight compensation with the rehabilitation robot ARMin. In Rehabilitation Robotics (ICORR), 2017 International Conference on. 2017, 72–77. BibTeX

    @inproceedings{just2017feedforward,
    	title = "Feedforward model based arm weight compensation with the rehabilitation robot ARMin",
    	author = {Just, Fabian and {\"O}zen, {\"O}zhan and Tortora, Stefano and Riener, Robert and Rauter, Georg},
    	booktitle = "Rehabilitation Robotics (ICORR), 2017 International Conference on",
    	pages = "72--77",
    	year = 2017,
    	organization = "IEEE"
    }
    


2016

  1. Stefano Michieletto, Francesca Stival, Francesco Castelli and Enrico Pagello. Teaching door abembly tasks in uncertain environment. In 47th International Symposium on Robotics, ISR 2016. 2016, 638–644. BibTeX

    @conference{11577_3256688,
    	abstract = "The paper describes our experience in the benchmarking phase of the European Robotics Challenges project. The main focus is on the original solution proposed for solving a door assembly task. The proposal has to deal with tolerances in the door and module positions, never seen before doors, fast and usable human-machine interfaces, legacy hardware in industrial scenarios, and valuable results in benchmarking activities.",
    	author = "Michieletto, Stefano and Stival, Francesca and Castelli, Francesco and Pagello, Enrico",
    	booktitle = "47th International Symposium on Robotics, ISR 2016",
    	keywords = "Artificial Intelligence; Human-Computer Interactio",
    	pages = "638--644",
    	publisher = "VDE Verlag GmbH",
    	title = "{Teaching door abembly tasks in uncertain environment}",
    	year = 2016
    }
    
  2. Francesca Stival, Stefano Michieletto and Enrico Pagello. Online subject-independent modeling of sEMG signals for the motion of a single robot joint. In Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics 2016-July. 2016, 1110–1116. DOI BibTeX

    @inproceedings{Stival2016,
    	author = "Stival, Francesca and Michieletto, Stefano and Pagello, Enrico",
    	booktitle = "Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics",
    	doi = "10.1109/BIOROB.2016.7523780",
    	isbn = 9781509032877,
    	issn = 21551774,
    	pages = "1110--1116",
    	title = "{Online subject-independent modeling of sEMG signals for the motion of a single robot joint}",
    	volume = "2016-July",
    	year = 2016
    }
    
  3. Elisa Tosello, Stefano Michieletto and Enrico Pagello. Training master students to program both virtual and real autonomous robots in a teaching laboratory. In IEEE Global Engineering Education Conference, EDUCON 10-13-Apri. 2016, 621–630. DOI BibTeX

    @inproceedings{Tosello2016,
    	author = "Tosello, Elisa and Michieletto, Stefano and Pagello, Enrico",
    	booktitle = "IEEE Global Engineering Education Conference, EDUCON",
    	doi = "10.1109/EDUCON.2016.7474615",
    	isbn = 9781467386333,
    	issn = 21659567,
    	keywords = "Aldebaran NAO,Constructivism,Educational Robotics,Humanoid,Lego Mindstorms NXT,Project-Based Learning,ROS,Vstone Robovie-X",
    	pages = "621--630",
    	title = "{Training master students to program both virtual and real autonomous robots in a teaching laboratory}",
    	volume = "10-13-Apri",
    	year = 2016
    }
    
  4. Stefano Michieletto, Elisa Tosello, Enrico Pagello and Emanuele Menegatti. Teaching humanoid robotics by means of human teleoperation through RGB-D sensors. Robotics and Autonomous Systems 75:671–678, 2016. DOI BibTeX

    @article{Michieletto2016,
    	abstract = "This paper presents a graduate course project on humanoid robotics offered by the University of Padova. The target is to safely lift an object by teleoperating a small humanoid. Students have to map human limbs into robot joints, guarantee the robot stability during the motion, and teleoperate the robot to perform the correct movement. We introduce the following innovative aspects with respect to classical robotic classes: i) the use of humanoid robots as teaching tools; ii) the simplification of the stable locomotion problem by exploiting the potential of teleoperation; iii) the adoption of a Project-Based Learning constructivist approach as teaching methodology. The learning objectives of both course and project are introduced and compared with the students' background. Design and constraints students have to deal with are reported, together with the amount of time they and their instructors dedicated to solve tasks. A set of evaluation results are provided in order to validate the authors' purpose, including the students' personal feedback. A discussion about possible future improvements is reported, hoping to encourage further spread of educational robotics in schools at all levels.",
    	author = "Michieletto, Stefano and Tosello, Elisa and Pagello, Enrico and Menegatti, Emanuele",
    	doi = "10.1016/j.robot.2015.09.023",
    	isbn = "0921-8890",
    	issn = 09218890,
    	journal = "Robotics and Autonomous Systems",
    	keywords = "Constructivism,Educational robotics,Humanoid,Kinect,NAO,Project-Based Learning,ROS,Robovie-X,Teleoperation",
    	pages = "671--678",
    	title = "{Teaching humanoid robotics by means of human teleoperation through RGB-D sensors}",
    	volume = 75,
    	year = 2016
    }
    
  5. Roberto Bortoletto, Stefano Michieletto, Enrico Pagello and Davide Piovesan. Human muscle-tendon stiffness estimation during normal gait cycle based on Gaussian mixture model. In Advances in Intelligent Systems and Computing 302. 2016, 1185–1197. DOI BibTeX

    @inproceedings{Bortoletto2016,
    	author = "Bortoletto, Roberto and Michieletto, Stefano and Pagello, Enrico and Piovesan, Davide",
    	booktitle = "Advances in Intelligent Systems and Computing",
    	doi = "10.1007/978-3-319-08338-4_86",
    	isbn = 9783319083377,
    	issn = 21945357,
    	keywords = "Gait cycle,Gaussian mixture model,Muscle stiffness",
    	pages = "1185--1197",
    	title = "{Human muscle-tendon stiffness estimation during normal gait cycle based on Gaussian mixture model}",
    	volume = 302,
    	year = 2016
    }
    
  6. Stefano Michieletto, Francesca Stival, Francesco Castelli and Enrico Pagello. Automated and Flexible Coil Winding Robotic Framework. In ISR 2018; 50th International Symposium on Robotics. 2016, 1–4. BibTeX

    @inproceedings{michieletto2016automated,
    	title = "Automated and Flexible Coil Winding Robotic Framework",
    	author = "Michieletto, Stefano and Stival, Francesca and Castelli, Francesco and Pagello, Enrico",
    	booktitle = "ISR 2018; 50th International Symposium on Robotics",
    	pages = "1--4",
    	year = 2016,
    	organization = "VDE"
    }
    


2015

  1. Riccardo Valentini, Stefano Michieletto, Fabiola Spolaor, Zimi Sawacha and Enrico Pagello. Processing of sEMG signals for online motion of a single robot joint through GMM modelization. In IEEE International Conference on Rehabilitation Robotics 2015-Septe. 2015, 943–949. DOI BibTeX

    @inproceedings{Valentini2015,
    	abstract = "This paper evaluates the use of Gaussian Mixture Model (GMM) trained through Electromyography (EMG) signals to online estimate the bending angle of a single human joint. The parameters involved in the evaluation are the number of Gaussian components, the channel used for model, the feature extraction method, and the size of the training set. The feature extraction is performed through Wavelet Transform by investigating several kind of configuration. Two set of experimental data are collected to validate the proposed framework from 6 different healthy subjects. Trained GMMs are validated by comparing the joint angle estimated through Gaussian Mixture Regression (GMR) with the one measured on new unseen data. The goodness of the estimated date are evaluated by means of Normalized Mean Square Error (NMSE), while the time performances of the retrieval system are measured at each phase in order to analyze possible critical situations. Achieved results show that our framework is able to obtain high performances in both accuracy and computation time. The whole procedure is tested on a real humanoid robot by remapping the human motion to the robotic platform in order to verify the proper execution of the original movement.",
    	author = "Valentini, Riccardo and Michieletto, Stefano and Spolaor, Fabiola and Sawacha, Zimi and Pagello, Enrico",
    	booktitle = "IEEE International Conference on Rehabilitation Robotics",
    	doi = "10.1109/ICORR.2015.7281325",
    	isbn = 9781479918072,
    	issn = 19457901,
    	pages = "943--949",
    	title = "{Processing of sEMG signals for online motion of a single robot joint through GMM modelization}",
    	volume = "2015-Septe",
    	year = 2015
    }
    
  2. Francesca Stival, Stefano Michieletto and Enrico Pagello. Subject-Independent Modeling of sEMG Signals for the Motion of a Single Robot Joint. In Workshop of Robotics: Science and Systems 2015 on Combining AI Reasoning and Cognitive Science with Robotics. 2015. URL BibTeX

    @conference{11577_3168471,
    	author = "Stival, Francesca and Michieletto, Stefano and Pagello, Enrico",
    	booktitle = "Workshop of Robotics: Science and Systems 2015 on Combining AI Reasoning and Cognitive Science with Robotics",
    	title = "{Subject-Independent Modeling of sEMG Signals for the Motion of a Single Robot Joint}",
    	url = "http://cogrobo.sabanciuniv.edu/wp-content/uploads/AI-CogSci-Robo{\_}2015{\_}poster{\_}1.pdf",
    	year = 2015
    }
    


2014

  1. Matteo Munaro, Morris Antonello, Michele Moro, Carlo Ferrari, Giorgio Clemente, Enrico Pagello and Emanuele Menegatti. FibreMap: Automatic Mapping of Fibre Orientation for Draping of Carbon Fibre Parts. July 2014, . BibTeX

    @inproceedings{FiberMap,
    	author = "Munaro, Matteo and Antonello, Morris and Moro, Michele and Ferrari, Carlo and Clemente, Giorgio and Pagello, Enrico and Menegatti, Emanuele",
    	year = 2014,
    	month = 07,
    	pages = "",
    	title = "FibreMap: Automatic Mapping of Fibre Orientation for Draping of Carbon Fibre Parts"
    }
    
  2. M Munaro, S Ghidoni, D T Dizmen and E Menegatti. A feature-based approach to people re-identification using skeleton keypoints. In 2014 IEEE International Conference on Robotics and Automation (ICRA) (). May 2014, 5644-5651. DOI BibTeX

    @inproceedings{6907689,
    	author = "M. Munaro and S. Ghidoni and D. T. Dizmen and E. Menegatti",
    	booktitle = "2014 IEEE International Conference on Robotics and Automation (ICRA)",
    	title = "A feature-based approach to people re-identification using skeleton keypoints",
    	year = 2014,
    	volume = "",
    	number = "",
    	pages = "5644-5651",
    	keywords = "image colour analysis;image recognition;image resolution;mobile robots;video surveillance;feature-based approach;people re-identification;skeleton keypoints;skeletal information;skeleton joints;compact feature-based signature;visible joint;state-of-the-art 2D feature descriptor;3D feature descriptor;public datasets;RGB-D sensor;public video surveillance dataset;resolution images;recognition accuracy;mobile robotics;Joints;Three-dimensional displays;Target tracking;Robots;Testing;Training",
    	doi = "10.1109/ICRA.2014.6907689",
    	issn = "1050-4729",
    	month = "May"
    }
    
  3. M Munaro, A Basso, A Fossati, Van L Gool and E Menegatti. 3D reconstruction of freely moving persons for re-identification with a depth sensor. In 2014 IEEE International Conference on Robotics and Automation (ICRA) (). May 2014, 4512-4519. DOI BibTeX

    @inproceedings{6907518,
    	author = "M. Munaro and A. Basso and A. Fossati and L. Van Gool and E. Menegatti",
    	booktitle = "2014 IEEE International Conference on Robotics and Automation (ICRA)",
    	title = "3D reconstruction of freely moving persons for re-identification with a depth sensor",
    	year = 2014,
    	volume = "",
    	number = "",
    	pages = "4512-4519",
    	keywords = "bone;cameras;image classification;image colour analysis;image sensors;object tracking;orthopaedics;RGB-D reidentification;skeleton feature descriptor;warped point cloud;skeletal tracking algorithm;long-term person reidentification;consumer depth sensor;3D freely moving person reconstruction;Three-dimensional displays;Training;Standards;Joints;Shape;Solid modeling",
    	doi = "10.1109/ICRA.2014.6907518",
    	issn = "1050-4729",
    	month = "May"
    }
    
  4. F Basso, A Pretto and E Menegatti. Unsupervised intrinsic and extrinsic calibration of a camera-depth sensor couple. In 2014 IEEE International Conference on Robotics and Automation (ICRA) (). May 2014, 6244-6249. DOI BibTeX

    @inproceedings{6907780,
    	author = "F. Basso and A. Pretto and E. Menegatti",
    	booktitle = "2014 IEEE International Conference on Robotics and Automation (ICRA)",
    	title = "Unsupervised intrinsic and extrinsic calibration of a camera-depth sensor couple",
    	year = 2014,
    	volume = "",
    	number = "",
    	pages = "6244-6249",
    	keywords = "calibration;cameras;estimation theory;image sensors;parameter estimation;reliability;unsupervised intrinsic calibration;unsupervised extrinsic calibration;camera-depth sensor couple;availability;RGB camera;Microsoft Kinect;robot;extrinsic parameter estimation;intrinsic parameter estimation;3D structure estimation;Robot sensing systems;Calibration;Three-dimensional displays;Cameras;Estimation;Systematics",
    	doi = "10.1109/ICRA.2014.6907780",
    	issn = "1050-4729",
    	month = "May"
    }
    
  5. Tosello Elisa, Bortoletto Roberto, Michieletto Stefano, Pagello Enrico and Menegatti Emanuele. An Integrated System to approach the Programming of Humanoid Robotics. In Proc. of Workshops of 13th Intelligent Autonomous Systems Conference. 2014, 93–100. URL BibTeX

    @conference{11577_2835795,
    	abstract = "This paper describes a set of laboratory experiences focused on humanoid robots offered at the University of Padua. Instructors developed an integrated system through which students can work with robots. The aim is to improve the educational experience introducing a new learning tool, namely a humanoid robot, and the Robots Operating System (ROS) in a constructivist framework. This approach to robotics teaching lets students exploiting up-to-date robotic technologies and to deal with multidisciplinary problems, applying a scientic approach. By using humanoid robots, students are able to compare human movements to robot motion. The comparison brings out human/robot similarities, pushing students to solve complex motion problems in a more natural way while discovering robot limitations. In this paper, the learning objectives of the project, and the tools used by the students are presented. A set of evaluation results are provided in order to validate the authors' purpose. Finally, a discussion about designed experiences and possible future improvements is reported, hoping to encourage further spread of educational robotics in schools at all levels.",
    	author = "Elisa, Tosello and Roberto, Bortoletto and Stefano, Michieletto and Enrico, Pagello and Emanuele, Menegatti",
    	booktitle = "Proc. of Workshops of 13th Intelligent Autonomous Systems Conference",
    	keywords = "Simulation; Humanoid Robots; Teaching Robotics; RO",
    	pages = "93--100",
    	publisher = "IT+Robotics srl",
    	title = "{An Integrated System to approach the Programming of Humanoid Robotics}",
    	url = "http://www.terecop.eu/TRTWR-RIE2014/files/00{\_}WFr1/00{\_}WFr1{\_}12.pdf",
    	year = 2014
    }
    
  6. Michieletto Stefano, Tosello Elisa, Romanelli Fabrizio, Ferrara Valentina and Menegatti Emanuele. ROS-I Interface for COMAU Robots. In Simulation, Modeling, and Programming for Autonomous Robots 8810. 2014, 243–254. DOI BibTeX

    @conference{11577_3156335,
    	abstract = "The following paper presents the ROS-I interface developed to control Comau manipulators. Initially, the Comau controller allowed users to command a real robot thanks to motion primitives formulated through a Comau motion planning library. Now, either a ROS or a non ROS -compliant platform can move either a real or a virtual Comau robot using any motion planning library. Comau modules have been wrapped within ROS and a virtual model of a Comau robot has been created. The manufacturer controller has been innovatively used to drive both the real and the simulated automata.",
    	author = "Stefano, Michieletto and Elisa, Tosello and Fabrizio, Romanelli and Valentina, Ferrara and Emanuele, Menegatti",
    	booktitle = "Simulation, Modeling, and Programming for Autonomous Robots",
    	doi = "10.1007/978-3-319-11900-7_21",
    	pages = "243--254",
    	publisher = "Davide Brugali, Jan F. Broenink, Torsten Kroeger, Bruce A. MacDonald",
    	title = "{ROS-I Interface for COMAU Robots}",
    	volume = 8810,
    	year = 2014
    }
    
  7. Stefano Ghidoni, Salvatore M Anzalone, Matteo Munaro, Stefano Michieletto and Emanuele Menegatti. A distributed perception infrastructure for robot assisted living. Robotics and Autonomous Systems 62(9):1316–1328, 2014. DOI BibTeX

    @article{Ghidoni2014,
    	abstract = "This paper presents an ambient intelligence system designed for assisted living. The system processes the audio and video data acquired from multiple sensors spread in the environment to automatically detect dangerous events and generate automatic warning messages. The paper presents the distributed perception infrastructure that has been implemented by means of an open-source software middleware called NMM. Different processing nodes have been developed which can cooperate to extract high level information about the environment. Examples of implemented nodes running algorithms for people detection or face recognition are presented. Experiments on novel algorithms for people fall detection and sound classification and localization are discussed. Eventually, we present successful experiments in two test bed scenarios. {\textcopyright} 2014 Elsevier B.V. All rights reserved.",
    	author = "Ghidoni, Stefano and Anzalone, Salvatore M. and Munaro, Matteo and Michieletto, Stefano and Menegatti, Emanuele",
    	doi = "10.1016/j.robot.2014.03.022",
    	issn = 09218890,
    	journal = "Robotics and Autonomous Systems",
    	keywords = "Ambient intelligence,Assisted living,Autonomous robots,Camera network,Distributed sensing,Intelligent autonomous systems",
    	number = 9,
    	pages = "1316--1328",
    	title = "{A distributed perception infrastructure for robot assisted living}",
    	volume = 62,
    	year = 2014
    }
    
  8. Stefano Michieletto, Stefano Ghidoni, Enrico Pagello, Michele Moro and Emanuele Menegatti. WHY TEACH ROBOTICS USING ROS?. Journal of Automation, Mobile Robotics & Intelligent Systems 8(1):60–68, 2014. URL BibTeX

    @article{Michieletto2014,
    	abstract = "This paper focuses on the key role played by the adoption of a framework in teaching robotics with a computer science approach in the master in Computer Engineering. The framework adopted is the Robot Operating System (ROS), which is becoming a standard de facto inside the robotics community. The educational activities proposed in this paper are based on a constructionist approach. The Mindstorms NXT robot kit is adopted to trigger the learning challenge. The ROS framework is exploited to drive the students programming methodology during the laboratory activities and to allow students to exercise with the major computer programming paradigms and the best programming practices. The major robotics topics students are involved with are: acquiring data from sensors, connecting sensors to the robot, and navigate the robot to reach the final goal. The positive effects given by this approach are highlighted in this paper by comparing the work recently produced by students with the work produced in the previous years in which ROS was not yet adopted and many different software tools and languages were used. The results of a questionnaire are reported showing that we achieved the didactical objectives we expected as instructors. [ABSTRACT FROM AUTHOR]",
    	author = "Michieletto, Stefano and Ghidoni, Stefano and Pagello, Enrico and Moro, Michele and Menegatti, Emanuele",
    	issn = 18978649,
    	journal = "Journal of Automation, Mobile Robotics {\&} Intelligent Systems",
    	keywords = "COMPUTER engineering,COMPUTER programming,COMPUTER science,COMPUTER software,Educational robotics,LEGO NXT robot,ROBOTICS in education,ROS,teaching robotics",
    	number = 1,
    	pages = "60--68",
    	title = "{WHY TEACH ROBOTICS USING ROS?}",
    	url = "10.14313/JAMRIS{\_}1-2014/8{\%}5Cnhttp://search.ebscohost.com/login.aspx?direct=true{\&}db=a9h{\&}AN=94617426{\&}lang=es{\&}site=ehost-live",
    	volume = 8,
    	year = 2014
    }
    
  9. Tosello Elisa, Michieletto Stefano, Bisson Andrea and Pagello Enrico. A Learning from Demonstration Framework for Manipulation Tasks. In ISR/Robotik 2014; 41st International Symposium on Robotics; Proceedings of. 2014, 1–7. BibTeX

    @conference{11577_3156336,
    	abstract = "This paper presents a Robot Learning from Demonstration (RLfD) framework for teaching manipulation tasks in an industrial environment: the system is able to learn a task performed by a human demonstrator and reproduce it through a manipulator robot. An RGB-D sensor acquires the scene (human in action); a skeleton tracking algorithm extracts the useful information from the images acquired (positions and orientations of skeleton joints); and this information is given as input to the motion re-targeting system that remaps the skeleton joints into the manipulator ones. After the remapping, a model for the robot motion controller is retrieved by applying first a Gaussian Mixture Model (GMM) and then a Gaussian Mixture Regression (GMR) on the collected data. Two types of controller are modeled: a position controller and a velocity one. The former was presented in [10] inclusive of simulation tests, and here it has been upgraded extended the proves to a real robot. The latter is proposed for the first time in this work and tested both in simulation and with the real robot. Experiments were performed using a Comau Smart5 SiX manipulator robot and let to show a comparison between the two controllers starting from natural human demonstrations.",
    	author = "Elisa, Tosello and Stefano, Michieletto and Andrea, Bisson and Enrico, Pagello",
    	booktitle = "ISR/Robotik 2014; 41st International Symposium on Robotics; Proceedings of",
    	pages = "1--7",
    	title = "{A Learning from Demonstration Framework for Manipulation Tasks}",
    	year = 2014
    }
    
  10. G Pozzato, S Michieletto, E Menegatti, F Dominio, G Marin, L Minto, S Milani and P Zanuttigh. Human-Robot Interaction with Depth-Based Gesture Recognition. In Proceedings of Real-Time gesture recognition for human-robot interaction workshop. 2014, 379–383. BibTeX

    @conference{11577_2926699,
    	abstract = "Human robot interaction is a very heterogeneous research field and it is attracting a growing interest. A key building block for a proper interaction between humans and robots is the automatic recognition and interpretation of gestures performed by the user. Consumer depth cameras (like MS Kinect) have made possible an accurate and reliable interpretation of human gestures. In this paper a novel framework for gesture- based human-robot interaction is proposed. Both hand gestures and full-body gestures are recognized through the use of depth information, and a human-robot interaction scheme based on these gestures is proposed. In order to assess the feasibility of the proposed scheme, the paper presents a simple application based on the well-known rock-scissors-paper game.",
    	author = "Pozzato, G and Michieletto, S and Menegatti, E and Dominio, F and Marin, G and Minto, L and Milani, S and Zanuttigh, P",
    	booktitle = "Proceedings of Real-Time gesture recognition for human-robot interaction workshop",
    	pages = "379--383",
    	publisher = "IT+Robotics srl",
    	title = "{Human-Robot Interaction with Depth-Based Gesture Recognition}",
    	year = 2014
    }
    
  11. Shaogang Gong, Marco Cristani, Shuicheng Yan and Chen Change Loy (eds.). One-Shot Person Re-identification with a Consumer Depth Camera. pages 161–181, Springer London, 2014. URL, DOI BibTeX

    @inbook{Munaro2014,
    	author = "Munaro, Matteo and Fossati, Andrea and Basso, Alberto and Menegatti, Emanuele and Van Gool, Luc",
    	editor = "Gong, Shaogang and Cristani, Marco and Yan, Shuicheng and Loy, Chen Change",
    	title = "One-Shot Person Re-identification with a Consumer Depth Camera",
    	booktitle = "Person Re-Identification",
    	year = 2014,
    	publisher = "Springer London",
    	address = "London",
    	pages = "161--181",
    	abstract = "In this chapter, we propose a comparison between two techniques for one-shot person re-identification from soft biometric cues. One is based upon a descriptor composed of features provided by a skeleton estimation algorithm; the other compares body shapes in terms of whole point clouds. This second approach relies on a novel technique we propose to warp the subject's point cloud to a standard pose, which allows to disregard the problem of the different poses a person can assume. This technique is also used for composing 3D models which are then used at testing time for matching unseen point clouds. We test the proposed approaches on an existing RGB-D re-identification dataset and on the newly built BIWI RGBD-ID dataset. This dataset provides sequences of RGB, depth, and skeleton data for 50 people in two different scenarios and it has been made publicly available to foster advancement in this new research branch.",
    	isbn = "978-1-4471-6296-4",
    	doi = "10.1007/978-1-4471-6296-4_8",
    	url = "https://doi.org/10.1007/978-1-4471-6296-4_8"
    }
    
  12. Matteo Munaro, Alex Horn, Randy Illum, Jeff Burke and Radu Bogdan Rusu. OpenPTrack : People Tracking for Heterogeneous Networks of Color-Depth Cameras. 2014. BibTeX

    @inproceedings{Munaro2014OpenPTrackP,
    	title = "OpenPTrack : People Tracking for Heterogeneous Networks of Color-Depth Cameras",
    	author = "Matteo Munaro and Alex Horn and Randy Illum and Jeff Burke and Radu Bogdan Rusu",
    	year = 2014
    }
    


2013

  1. Munaro Matteo, Ballin Gioia, Michieletto Stefano and Menegatti Emanuele. 3D flow estimation for human action recognition from colored point clouds. BIOLOGICALLY INSPIRED COGNITIVE ARCHITECTURES 5:42–51, 2013. URL, DOI BibTeX

    @article{11577_2668256,
    	abstract = "Motion perception and classification are key elements exploited by humans for recognizing actions. The same principles can serve as a basis for building cognitive architectures which can recognize human actions, thus enhancing challenging applications such as human robot interaction, visual surveillance, content-based video analysis and motion capture. In this paper, we propose an autonomous system for real-time human action recognition based on 3D motion flow estimation. We exploit colored point cloud data acquired with a Microsoft Kinect and we summarize the motion information by means of a 3D grid-based descriptor. Finally, temporal sequences of descriptors are classified with the Nearest Neighbor technique. We also present a newly created public dataset for RGB-D human action recognition which contains 15 actions performed by 12 different people. Our overall system is tested on this dataset and on the dataset used in Ballin, Munaro, and Menegatti (2012), showing the effectiveness of the proposed approach in recognizing about 90{\%} of the actions.",
    	author = "Matteo, Munaro and Gioia, Ballin and Stefano, Michieletto and Emanuele, Menegatti",
    	doi = "10.1016/j.bica.2013.05.008",
    	journal = "BIOLOGICALLY INSPIRED COGNITIVE ARCHITECTURES",
    	keywords = "Action recognition; Colored point clouds; RGB-D da",
    	pages = "42--51",
    	publisher = "Elsevier Ltd",
    	title = "{3D flow estimation for human action recognition from colored point clouds}",
    	url = "http://www.sciencedirect.com/science/article/pii/S2212683X13000431",
    	volume = 5,
    	year = 2013
    }
    
  2. Munaro Matteo, Michieletto Stefano and Menegatti Emanuele. An evaluation of 3D motion flow and 3D pose estimation for human action recognition. In RSS Workshops: RGB-D: Advanced Reasoning with Depth Cameras.. 2013. URL BibTeX

    @conference{11577_2718093,
    	abstract = "Modern human action recognition algorithms which exploit 3D information mainly classify video sequences by extract- ing local or global features from the RGB-D domain or classifying the skeleton information provided by a skeletal tracker. In this paper, we propose a comparison between two techniques which share the same classification process, while differing in the type of descriptor which is classified. The former exploits an improved version of a recently proposed approach for 3D motion flow estimation from colored point clouds, while the latter relies on the estimated skeleton joints positions. We compare these methods on a newly created dataset for RGB-D human action recognition which contains 15 actions performed by 12 different people.",
    	author = "Matteo, Munaro and Stefano, Michieletto and Emanuele, Menegatti",
    	booktitle = "RSS Workshops: RGB-D: Advanced Reasoning with Depth Cameras.",
    	keywords = "service robotics; Action recognition; 3D motion fl",
    	title = "{An evaluation of 3D motion flow and 3D pose estimation for human action recognition}",
    	url = "http://www.cs.washington.edu/ai/Mobile{\_}Robotics/rgbd-workshop-2013/papers/Munaro{\_}et{\_}al.pdf",
    	year = 2013
    }
    
  3. Michieletto Stefano, Rizzi Alberto and Menegatti Emanuele. Robot learning by observing humans activities and modeling failures. In IROS workshops: Cognitive Robotics Systems (CRS2013). 2013. URL BibTeX

    @conference{11577_2717878,
    	abstract = "People needs are varied and different. Service robotics aims to help people to satisfy these needs, but not all the feasible programs can be preloaded into a robot. The robot have to learn new tasks depending on the circumstances. A solution to this challenge could be Robot Learning from Demonstration (RLfD). In this paper, a RLfD framework is described in its entire pipeline. The data are acquired from a low cost RGB-D sensor, so the user can act naturally with no need of additional hardware. The information are subsequently elaborated to adapt to the robot structure and modeled to overcome the differences between human and robot. Experiments are performed using input data coming from a publicly available dataset of human actions, and a humanoid robot, an Aldebaran NAO, is shown to successfully replicate an action based on human demonstrations and some further trials automatically generated from the learned model.",
    	author = "Stefano, Michieletto and Alberto, Rizzi and Emanuele, Menegatti",
    	booktitle = "IROS workshops: Cognitive Robotics Systems (CRS2013)",
    	keywords = "Robot Learning from Demonstration; RGB-D sensor; G",
    	title = "{Robot learning by observing humans activities and modeling failures}",
    	url = "http://crs2013.org/papers/Michieletto.pdf",
    	year = 2013
    }
    
  4. S Michieletto, S Ghidoni, E Pagello, M Moro and E Menegatti. Why teach robotics using ROS. In Proceedings of the 4th International Conference on Robotics in Education. 2013, 145–151. URL BibTeX

    @conference{11577_2836673,
    	abstract = "This paper focuses on the key role played by the adoption of a framework in teaching robotics with a computer science approach in the master in Computer Engineeering. The framework adopted is the Robot Operating System (ROS), which is becoming a standard de facto inside the robotics community. The educational activities proposed in this paper are based on a constructionist approach. The Mindstorms NXT robot kit is adopted to trigger the learning challenge. The ROS framework is exploited to drive the students programming methodology during the laboratory activities and to allow students to exercise with the major computer programming paradigms and the best programming practices. The major robotics topics students are involved with are: acquiring data from sensors, connecting sensors to the robot, and navigate the robot to reach the final goal. The positive effects given by this approach are highlighted in this paper by comparing the work recently produced by students with the work produced in the previous years in which ROS was not yet adopted and many different software tools and languages were used. The results of a questionnaire are reported showing that we achieved the didactical objectives we expected as instructors.",
    	author = "Michieletto, S and Ghidoni, S and Pagello, E and Moro, M and Menegatti, E",
    	booktitle = "Proceedings of the 4th International Conference on Robotics in Education",
    	keywords = "Educational robotics; ROS; LEGO Mindstorms NXT; te",
    	pages = "145--151",
    	publisher = "Faculty of Electrical, Electronic, Computer and Control Engineering, {\L}{\'{o}}d{\'{z}}, Poland",
    	title = "{Why teach robotics using ROS}",
    	url = "http://rie2013.eu/",
    	year = 2013
    }
    
  5. Michieletto Stefano, Zanin Davide and Menegatti Emanuele. NAO robot simulation for service robotics purposes. In Proc. of European Modelling Symposium EMS2013 (EMS2013). 2013, 448–453. DOI BibTeX

    @conference{11577_2718088,
    	abstract = "Humanoids playing soccer are required to solve a great variety of tasks: from perception to body motion, from decision making to team coordination. On the other hand, results from this community are sometimes underestimated or unexploited because of the dedicated software developed. In particular simulators are often designed for a specific robotics platform or in some other cases the integration with existing software and frameworks is hard to implement and time consuming. In this paper we introduce a novel virtual model to simulate the humanoid robot Aldebaran NAO. The URDF (Unified Robot Description Format) standard has been followed in order to maintain the model as general purpose as possible. Related plug-ins to make it works in Gazebo and V-REP simulation environments were also developed in order to test the model under ROS (Robot Operating System), a very common robotics framework.",
    	author = "Stefano, Michieletto and Davide, Zanin and Emanuele, Menegatti",
    	booktitle = "Proc. of European Modelling Symposium EMS2013 (EMS2013)",
    	doi = "10.1109/EMS.2013.80",
    	keywords = "computer simulations; Aldebaran NAO; virtual model",
    	pages = "448--453",
    	publisher = "IEEE",
    	title = "{NAO robot simulation for service robotics purposes}",
    	year = 2013
    }
    
  6. Bisson Andrea, Busatto Andrea, Michieletto Stefano and Menegatti Emanuele. Stabilize Humanoid Robot Teleoperated by a RGB-D Sensor. In CEUR WORKSHOP PROCEEDINGS 1107. 2013, 97–102. URL BibTeX

    @conference{11577_2717682,
    	abstract = "An easy way to let a robot execute complex actions is to let the robot copy human moves. Useful information are read by sensors and elaborated to convert them into robot movements. This work focuses on keeping the robot balanced while it is performing an action: grasp an object laying on the ground in front of the robot. Experiments are performed with a human user moving in front of the sensor using a humanoid robot performing the same action, the Vstone Robovie-X.",
    	author = "Andrea, Bisson and Andrea, Busatto and Stefano, Michieletto and Emanuele, Menegatti",
    	booktitle = "CEUR WORKSHOP PROCEEDINGS",
    	keywords = "RGB-D sensor; Vstone Robovie-X; humanoids; stabili",
    	pages = "97--102",
    	title = "{Stabilize Humanoid Robot Teleoperated by a RGB-D Sensor}",
    	url = "http://ceur-ws.org/Vol-1107/paper12.pdf",
    	volume = 1107,
    	year = 2013
    }
    
  7. Edmond Wai Yan So, Matteo Munaro, Stefano Michieletto, Stefano Tonello and Emanuele Menegatti. 3DComplete: Efficient completeness inspection using a 2.5D color scanner. Computers in Industry 64(9):1237–1252, 2013. DOI BibTeX

    @article{YanSo2013,
    	abstract = "In this paper, we present a low-cost and highly configurable quality inspection system capable of capturing 2.5D color data, created using off-the-shelf machine vision components, open-source software libraries, and a combination of standard and novel algorithms for 2.5D data processing. The system uses laser triangulation to capture 3D depth, in parallel with a color camera and a line light projector to capture color texture, which are then combined into a color 2.5D model in real-time. Using many examples of completeness inspection tasks that are extremely difficult to solve with current 2D-based methods, we demonstrate how the 2.5D images and point clouds generated by our system can be used to solve these complex tasks effectively and efficiently. Our system is currently being integrated into a real production environment, showing that completeness inspection incorporating 3D technology can be readily achieved in a short time at low costs. {\textcopyright} 2013 Elsevier B.V. All rights reserved.",
    	author = "{Yan So}, Edmond Wai and Munaro, Matteo and Michieletto, Stefano and Tonello, Stefano and Menegatti, Emanuele",
    	doi = "10.1016/j.compind.2013.03.014",
    	issn = 01663615,
    	journal = "Computers in Industry",
    	keywords = "3D reconstruction,Completeness inspection,Image and range data fusion,Laser triangulation",
    	number = 9,
    	pages = "1237--1252",
    	title = "{3DComplete: Efficient completeness inspection using a 2.5D color scanner}",
    	volume = 64,
    	year = 2013
    }
    
  8. Edmond Wai Yan So, Matteo Munaro, Stefano Michieletto, Mauro Antonello and Emanuele Menegatti. Real-time 3D model reconstruction with a dual-laser triangulation system for assembly line completeness inspection. In Advances in Intelligent Systems and Computing 194 AISC(VOL. 2). 2013, 707–716. DOI BibTeX

    @inproceedings{So2013,
    	author = "So, Edmond Wai Yan and Munaro, Matteo and Michieletto, Stefano and Antonello, Mauro and Menegatti, Emanuele",
    	booktitle = "Advances in Intelligent Systems and Computing",
    	doi = "10.1007/978-3-642-33932-5_66",
    	isbn = 9783642339318,
    	issn = 21945357,
    	number = "VOL. 2",
    	pages = "707--716",
    	title = "{Real-time 3D model reconstruction with a dual-laser triangulation system for assembly line completeness inspection}",
    	volume = "194 AISC",
    	year = 2013
    }
    
  9. Matteo Munaro, Filippo Basso and Stefano Michieletto. A software architecture for RGB-D people tracking based on ros framework for a mobile robot. Frontiers of Intelligent łdots, 2013. URL BibTeX

    @article{Munaro2013a,
    	abstract = "This paper describes the software architecture of a distributed multi-people tracking algorithm for mobile platforms equipped with a RGB-D sensor. Our approach features an efficient point cloud depth-based clus-tering, an HOG-like classification to robustly initialize a person tracking and a person classifier with online learning to drive data association. We explain in details how ROS functionalities and tools play an important role in the possibility of the software to be real time, distributed and easy to configure and debug. Tests are presented on a challenging real-world indoor environment and track-ing results have been evaluated with the CLEAR MOT metrics. Our algo-rithm proved to correctly track 96{\%} of people with very limited ID switches and few false positives, with an average frame rate above 20 fps. We also test and discuss its applicability to robot-people following tasks and we re-port experiments on a public RGB-D dataset proving that our software can be distributed in order to increase the framerate and decrease the data ex-change when multiple sensors are used.",
    	author = "Munaro, Matteo and Basso, Filippo and Michieletto, Stefano",
    	journal = "Frontiers of Intelligent {\ldots}",
    	keywords = "1 introduction and related,autonomous service robots have,data,in dynamic and populated,mobile robots,people tracking,real-time,rgb-d,robot operating system,to move and act,work",
    	title = "{A software architecture for RGB-D people tracking based on ros framework for a mobile robot}",
    	url = "http://link.springer.com/chapter/10.1007/978-3-642-35485-4{\_}5",
    	year = 2013
    }
    
  10. Filippo Basso, Matteo Munaro, Stefano Michieletto, Enrico Pagello and Emanuele Menegatti. Fast and robust multi-people tracking from RGB-D data for a mobile robot. In Advances in Intelligent Systems and Computing 193 AISC(VOL. 1). 2013, 265–276. DOI BibTeX

    @inproceedings{Basso2013,
    	abstract = "This paper proposes a fast and robust multi-people tracking algorithm for mobile platforms equipped with a RGB-D sensor. Our approach features an efficient point cloud depth-based clustering, an HOG-like classification to robustly initialize a person tracking and a person classifier with online learning to manage the person ID matching even after a full occlusion. For people detection, we make the assumption that people move on a ground plane. Tests are presented on a challenging real-world indoor environment and results have been evaluated with the CLEAR MOT metrics. Our algorithm proved to correctly track 96{\%} of people with very limited ID switches and few false positives, with an average frame rate of 25 fps. Moreover, its applicability to robot-people following tasks have been tested and discussed.",
    	author = "Basso, Filippo and Munaro, Matteo and Michieletto, Stefano and Pagello, Enrico and Menegatti, Emanuele",
    	booktitle = "Advances in Intelligent Systems and Computing",
    	doi = "10.1007/978-3-642-33926-4_25",
    	isbn = 9783642339257,
    	issn = 21945357,
    	keywords = "People tracking,RGB-D data,mobile robots,real-time",
    	number = "VOL. 1",
    	pages = "265--276",
    	title = "{Fast and robust multi-people tracking from RGB-D data for a mobile robot}",
    	volume = "193 AISC",
    	year = 2013
    }
    
  11. Pozzato Gabriele, Michieletto Stefano and Menegatti Emanuele. Towards Smart Robots: Rock-Paper-Scissors Gaming versus Human Players. In CEUR WORKSHOP PROCEEDINGS 1107. 2013, 89–95. URL BibTeX

    @conference{11577_2717681,
    	abstract = "In this project a human robot interaction system was developed in order to let people naturally play rock-paper-scissors games against a smart robotic opponent. The robot does not perform random choices, the system is able to analyze the previous rounds trying to forecast the next move. A Machine Learning algorithm based on Gaussian Mixture Model (GMM) allows us to increase the percentage of robot victories. This is a very important aspect in the natural interaction between human and robot, in fact, people do not like playing against “stupid” machines, while they are stimulated in confronting with a skilled opponent.",
    	author = "Gabriele, Pozzato and Stefano, Michieletto and Emanuele, Menegatti",
    	booktitle = "CEUR WORKSHOP PROCEEDINGS",
    	keywords = "Gaussian Mixture Model; Machine Learning; human ro",
    	pages = "89--95",
    	title = "{Towards Smart Robots: Rock-Paper-Scissors Gaming versus Human Players}",
    	url = "http://ceur-ws.org/Vol-1107/paper11.pdf",
    	volume = 1107,
    	year = 2013
    }
    
  12. Michieletto Stefano, Chessa Nicola and Menegatti Emanuele. Learning how to approach industrial robot tasks from natural demonstrations. In 2013 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO). 2013, 255–260. DOI BibTeX

    @conference{11577_2718084,
    	abstract = "In the last years, Robot Learning from Demonstration (RLfD) has become a major topic in robotics research. The main reason for this is that programming a robot can be a very difficult and time spending task. The RLfD paradigm has been applied to a great variety of robots, but it is still difficult to make the robot learn a task properly. Often the teacher is not an expert in the field, and viceversa an expert could not know well enough the robot to be a teacher. With this paper, we aimed at closing this gap by proposing a novel motion re-targeting technique to make a manipulator learn from natural demonstrations. A RLfD framework based on Gaussian Mixture Models (GMM) and Gaussian Mixture Regressions (GMR) was set to test the accuracy of the system in terms of precision and repeatability. The robot used during the experiments is a Comau Smart5 SiX and a novel virtual model of this manipulator has also been developed to simulate an industrial scenario which allows valid experimentation while avoiding damages to the real robot.",
    	author = "Stefano, Michieletto and Nicola, Chessa and Emanuele, Menegatti",
    	booktitle = "2013 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO)",
    	doi = "10.1109/ARSO.2013.6705538",
    	keywords = "Robot Learning from Demonstration; industrial mani",
    	pages = "255--260",
    	title = "{Learning how to approach industrial robot tasks from natural demonstrations}",
    	year = 2013
    }
    
  13. Stefano Michieletto, Nicola Chessa and Emanuele Menegatti. Learning how to approach industrial robot tasks from natural demonstrations. In Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO. 2013, 255–260. DOI BibTeX

    @inproceedings{Michieletto2013,
    	abstract = "In the last years, Robot Learning from Demon-$\backslash$nstration (RLfD) has become a major topic in robotics research. The main reason for this is that programming a robot can be a very difficult and time spending task.$\backslash$nThe RLfD paradigm has been applied to a great variety of robots, but it is still difficult to make the robot learn a task properly. Often the teacher is not an expert in the field, and viceversa an expert could not know well enough the robot to be a teacher.$\backslash$nWith this paper, we aimed at closing this gap by proposing a novel motion re-targeting technique to make a manipulator learn from natural demonstrations. A RLfD framework based$\backslash$non Gaussian Mixture Models (GMM) and Gaussian Mixture Regressions (GMR) was set to test the accuracy of the system in terms of precision and repeatability.$\backslash$nThe robot used during the experiments is a Comau Smart5 SiX and a novel virtual model of this manipulator has also been developed to simulate an industrial scenario which allows valid$\backslash$nexperimentation while avoiding damages to the real robot.",
    	author = "Michieletto, Stefano and Chessa, Nicola and Menegatti, Emanuele",
    	booktitle = "Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO",
    	doi = "10.1109/ARSO.2013.6705538",
    	isbn = 9781479923694,
    	issn = 21627568,
    	pages = "255--260",
    	title = "{Learning how to approach industrial robot tasks from natural demonstrations}",
    	year = 2013
    }
    
  14. E So, M Munaro, S Michieletto, S Tonello and E Menegatti. 3DComplete: Efficient Completeness Inspection using a 2.5D Color Scanner. COMPUTERS IN INDUSTRY 64:1237–1252, 2013. URL, DOI BibTeX

    @article{11577_2574234,
    	abstract = "In this paper, we present a low-cost and highly configurable quality inspection system capable of capturing 2.5D color data, created using off-the-shelf machine vision components, open-source software libraries, and a combination of standard and novel algorithms for 2.5D data processing. The system uses laser triangulation to capture 3D depth, in parallel with a color camera and a line light projector to capture color texture, which are then combined into a color 2.5D model in real- time. Using many examples of completeness inspection tasks that are extremely difficult to solve with current 2D-based methods, we demonstrate how the 2.5D images and point clouds generated by our system can be used to solve these complex tasks effectively and efficiently. Our system is currently being integrated into a real production environment, showing that completeness inspection incorporating 3D technology can be readily achieved in a short time at low costs.",
    	author = "So, E and Munaro, M and Michieletto, S and Tonello, S and Menegatti, E",
    	doi = "10.1016/j.compind.2013.03.014",
    	journal = "COMPUTERS IN INDUSTRY",
    	keywords = "Completeness inspection; 3D reconstruction; Image",
    	pages = "1237--1252",
    	publisher = "Elsevier",
    	title = "{3DComplete: Efficient Completeness Inspection using a 2.5D Color Scanner}",
    	url = "http://link.springer.com/chapter/10.1007/978-1-4471-6741-9{\_}7",
    	volume = 64,
    	year = 2013
    }
    
  15. Matteo Comin and Morris Antonello. Fast Computation of Entropic Profiles for the Detection of Conservation in Genomes. In Alioune Ngom, Enrico Formenti, Jin-Kao Hao, Xing-Ming Zhao and Twan Laarhoven (eds.). Pattern Recognition in Bioinformatics. 2013, 277–288. BibTeX

    @inproceedings{10.1007/978-3-642-39159-0_25,
    	author = "Comin, Matteo and Antonello, Morris",
    	editor = "Ngom, Alioune and Formenti, Enrico and Hao, Jin-Kao and Zhao, Xing-Ming and van Laarhoven, Twan",
    	title = "Fast Computation of Entropic Profiles for the Detection of Conservation in Genomes",
    	booktitle = "Pattern Recognition in Bioinformatics",
    	year = 2013,
    	publisher = "Springer Berlin Heidelberg",
    	address = "Berlin, Heidelberg",
    	pages = "277--288",
    	abstract = "The information theory has been used for quite some time in the area of computational biology. In this paper we discuss and improve the function Entropic Profile, introduced by Vinga and Almeida in [23]. The Entropic Profiler is a function of the genomic location that captures the importance of that region with respect to the whole genome. We provide a linear time linear space algorithm called Fast Entropic Profile, as opposed to the original quadratic implementation. Moreover we propose an alternative normalization that can be also efficiently implemented. We show that Fast EP is suitable for large genomes and for the discovery of motifs with unbounded length.",
    	isbn = "978-3-642-39159-0"
    }
    


2012

  1. Basso Filippo, Munaro Matteo, Michieletto Stefano, Pagello Enrico and Menegatti Emanuele. Fast and Robust Multi-people Tracking from RGB-D Data for a Mobile Robot. In ADVANCES IN INTELLIGENT SYSTEMS AND COMPUTING 193. 2012, 265–276. URL, DOI BibTeX

    @conference{11577_2533616,
    	abstract = "This paper proposes a fast and robust multi-people tracking algorithm for mobile platforms equipped with a RGB-D sensor. Our approach features an efficient point cloud depth-based clustering, an HOG-like classification to robustly initialize a person tracking and a person classifier with online learning to manage the person ID matching even after a full occlusion. For people detection, we make the assumption that people move on a ground plane. Tests are presented on a challenging real-world indoor environment and results have been evaluated with the CLEAR MOT metrics. Our algorithm proved to correctly track 96{\%} of people with very limited ID switches and few false positives, with an average frame rate of 25 fps. Moreover, its applicability to robot-people following tasks have been tested and discussed.",
    	author = "Filippo, Basso and Matteo, Munaro and Stefano, Michieletto and Enrico, Pagello and Emanuele, Menegatti",
    	booktitle = "ADVANCES IN INTELLIGENT SYSTEMS AND COMPUTING",
    	doi = "10.1007/978-3-642-33926-4_25",
    	pages = "265--276",
    	publisher = "Springer Berlin Heidelberg",
    	title = "{Fast and Robust Multi-people Tracking from RGB-D Data for a Mobile Robot}",
    	url = "http://link.springer.com/chapter/10.1007{\%}2F978-3-642-33926-4{\_}25",
    	volume = 193,
    	year = 2012
    }
    
  2. Edmond Wai Yan So, Munaro Matteo, Michieletto Stefano, Antonello Mauro and Menegatti Emanuele. Real-Time 3D Model Reconstruction with a Dual-Laser Triangulation System for Assembly Line Completeness Inspection. In ADVANCES IN INTELLIGENT SYSTEMS AND COMPUTING 194. 2012, 707–716. URL, DOI BibTeX

    @conference{11577_2533672,
    	abstract = "In this paper, we present an improved version of our Dual Laser Triangulation System, a low-cost color 3D model acquisition system built with commonly available machine vision products. The system produces a color point cloud model of scanned objects that can be used to perform completeness inspection tasks on assembly lines. In particular, we show that model acquisition and reconstruction can be achieved in real-time using such a low-cost solution. Our results demonstrate that 3D-based inspection can be achieved readily and economically in a real industrial production environment.",
    	address = "Berlin",
    	author = "{Edmond Wai Yan So} and Matteo, Munaro and Stefano, Michieletto and Mauro, Antonello and Emanuele, Menegatti",
    	booktitle = "ADVANCES IN INTELLIGENT SYSTEMS AND COMPUTING",
    	doi = "10.1007/978-3-642-33932-5_66",
    	pages = "707--716",
    	publisher = "Springer Verlag",
    	title = "{Real-Time 3D Model Reconstruction with a Dual-Laser Triangulation System for Assembly Line Completeness Inspection}",
    	url = "http://link.springer.com/chapter/10.1007{\%}2F978-3-642-33932-5{\_}66",
    	volume = 194,
    	year = 2012
    }
    
  3. Edmond Wai Yan So, Stefano Michieletto and Emanuele Menegatti. Calibration of a dual-laser triangulation system for assembly line completeness inspection. In 2012 IEEE International Symposium on Robotic and Sensors Environments, ROSE 2012 - Proceedings. 2012, 138–143. DOI BibTeX

    @inproceedings{So2012,
    	author = "So, Edmond Wai Yan and Michieletto, Stefano and Menegatti, Emanuele",
    	booktitle = "2012 IEEE International Symposium on Robotic and Sensors Environments, ROSE 2012 - Proceedings",
    	doi = "10.1109/ROSE.2012.6402621",
    	isbn = 9781467327046,
    	keywords = "conveyor calibration,dual lasers,laser calibration,laser triangulation,misalignment",
    	pages = "138--143",
    	title = "{Calibration of a dual-laser triangulation system for assembly line completeness inspection}",
    	year = 2012
    }
    
  4. Stefano Michieletto and Emanuele Menegatti. Human action recognition oriented to humanoid robots action reproduction. In CEUR Workshop Proceedings 860. 2012, 35–40. BibTeX

    @inproceedings{Michieletto2012,
    	abstract = "Our research aims at providing a humanoid robot with the ability of observing, learning, and reproducing actions performed by humans in order to acquire new skills. In other words, we want to apply artificial intelligence techniques to automatically recognize a human activity in order to make a humanoid robot able to reproduce it.This system has not only to distinguish between different actions, but also to represent them in a proper manner to allow a robot to reproduce the motion trajectories the demonstrator showed and learn new skills. Since the final system is going to be integrated in an autonomous humanoid robot (specifically model Aldebran Nao), we are working with an RGB-D sensor (Microsoft Kinect) that can be easily applied to it. This objective introduces also strict real-time constrains to the action recognition algorithm: we have opted for a probabilistic approach that offers good modeling and fast recognition performances.",
    	author = "Michieletto, Stefano and Menegatti, Emanuele",
    	booktitle = "CEUR Workshop Proceedings",
    	issn = 16130073,
    	keywords = "Action recognition,Humanoid robots,Imitation learning,Programming by demonstration",
    	pages = "35--40",
    	title = "{Human action recognition oriented to humanoid robots action reproduction}",
    	volume = 860,
    	year = 2012
    }
    


2011

  1. Munaro Matteo, Michieletto Stefano, So Edmond, Alberton Daniele and Menegatti Emanuele. Fast 2.5D model reconstruction of assembled parts with high occlusion for completeness inspection. In Proc. of World Academy of Science, Engineering and Technology. 2011, 1718–1724. BibTeX

    @conference{11577_2534856,
    	abstract = "In this work a dual laser triangulation system is pre- sented for fast building of 2.5D textured models of objects within a production line. This scanner is designed to produce data suitable for 3D completeness inspection algorithms. For this purpose two laser projectors have been used in order to considerably reduce the problem of occlusions in the camera movement direction. Results of reconstruction of electronic boards are presented, together with a comparison with a commercial system.",
    	author = "Matteo, Munaro and Stefano, Michieletto and Edmond, So and Daniele, Alberton and Emanuele, Menegatti",
    	booktitle = "Proc. of World Academy of Science, Engineering and Technology",
    	keywords = "3D quality inspection; 2.5D reconstruction; laser",
    	pages = "1718--1724",
    	publisher = "World Academy of Science Engineering and Technology",
    	title = "{Fast 2.5D model reconstruction of assembled parts with high occlusion for completeness inspection}",
    	year = 2011
    }
    

Si terrà mercoledì 5, giovedì 6 e venerdì 7 settembre 2018 presso il Dipartimento di Ingegneria dell'Informaziomne la Sesta Edizione del Corso di Formazione per Insegnanti Introduzione della Robotica Educativa nella Didattica Istituzionale. E' aperto a insegnanti di tutte le materie e di ogni ordine e grado. La Robotica Educativa, infatti, può essere uno straordinario strumento didattico disciplinare, anche per materie che non sembrano avere affinità con essa. Dopo il corso, resterà a disposizione uno sportello online per rispondere a domande e discutere situazioni applicative reali.

Maggiori dettagli al link http://robotics.dei.unipd.it/index.php/teaching/15-educational-robotics/140-roboticaeducativa2018

Trovate qui la Scheda di pre-iscrizione, che va inviata entro il 4 giugno. Chi verrà selezionato sarà avvisato personalmente.

 

Abstract

To retrieve the 3D coordinates of an object in the robot workspace is a fundamental capability for industrial and service applications. This can be achieved by means of a camera mounted on the robot end-effector only if the hand-eye transformation is known. The standard calibration process requires to view a calibration pattern, e.g. a checkerboard, from several different perspectives. This work extends the standard approach performing calibration pattern localization and hand-eye calibration in a fully automatic way. A two phase procedure has been developed and tested in both simulated and real scenarios, demonstrating that the automatic calibration reaches the same performance level of a standard procedure, while avoiding any human intervention. As a final contribution, the source code for an automatic and robust calibration is released.

 

Software

Here, you can find the ROS project hand_eye_calib.

 

Licence

The software is freely available for academic use.
For questions about the tool, please contact This email address is being protected from spambots. You need JavaScript enabled to view it..

 

Reference

@inproceedings{antonello2017autohandeye,
  title={A Fully Automatic Hand-Eye Calibration System},
  author={Antonello, Morris and Gobbi, Andrea and Michieletto, Stefano and Ghidoni, Stefano and Menegatti, Emanuele},
  booktitle={To appear in Mobile Robots (ECMR), 2017 European Conference on},
  year={2017},
}

The IASLAB-RGBD Fallen Person Dataset consists of several RGB-D frame sequences containing 15 different people. It has been acquired in two different laboratory environments, the Lab A and Lab B. It can be divided into two parts: the former acquired from 3 static Kinect One V2 placed on 3 different pedestals ; the latter from a Kinect One V2 mounted on our healthcare robot prototype, see "An Open Source Robotic Platform for Ambient Assisted Living" by M. Carraro, M. Antonello et al in AIRO at AI*IA 2015.

 

Both parts are briefly described in the following. They contain the training/test splits of our approach to detect fallen people.

STATIC DATASET:

  • Folder "raw": 360 RGB frames and point clouds with the camera calibrations;
  • Folder "segmented_fallen_people": point clouds of the fallen people. They have been manually segmented;
  • Folder "training_with_cad_room_and_nyudv2": random selected positives (70%), 24 point clouds from the Lab A and 31 point clouds from the NYU Depth Dataset V2 by Silberman et al;
  • Folder "test_with_lab_room": random selected positives (30%) and 32 point clouds from the Lab B.

DYNAMIC DATASET:

  • Folder "training": 4 ROS bags with 15932 RGB-D frames in total acquired during 4 robot patrollings of the Lab A;
  • Folder "test": 4 ROS bags with 9391 RGB-D frames in total acquired during 4 robot patrollings of the Lab B. This room is more similar to an apartament: spaces are smaller, it is cluttered and contains a sofa;
  • Folder "maps": 2D maps of the two environments and ground truth positions of the person centroids in the maps.

Download links:

StaticDataset

DynamicDatasetPart1

DynamicDatasetPart2

 

In the figures below, some RGB samples from both environments are reported:

 1487936496.882732   1487934554.500764   1487935479.169314   1487935432.170219

 

For questions and remarks directly related to the IASLAB-RGBD Fallen Person Dataset, please contact This email address is being protected from spambots. You need JavaScript enabled to view it. and This email address is being protected from spambots. You need JavaScript enabled to view it..

 

Licence

This dataset is freely available for academic use. 

 

References

If you use this dataset, please cite the following work:

@inproceedings{antonello2017fast,
 title={Fast and Robust detection of fallen people from a mobile robot},
 author={Antonello, Morris and Carraro, Marco and Pierobon, Marco and Menegatti, Emanuele},
 booktitle={Intelligent Robots and Systems (IROS), 2017 IEEE/RSJ International Conference on},
 year={2017},
 organization={IEEE}
}

Header

 

IT+Robotics is a spin-off company of the University of Padua. It was created in 2005 by professors working in the field of robotics and young, brilliant people coming from the information engineering department of the University of Padua.

The mission is the technology transfer from University to business. Innovation boosted by cutting edge technology, that was a prerogative of academia only few years ago, is the right way towards growth, and will let us to contrast the current crisis.

The IT+Robotics team, a mix of scientists and developers, is able to provide advanced solutions to the problems, thanks to the experience gained during years of research and industrial development in the field of autonomous robotics: real-time operating systems, artificial vision systems, software agents management, and highly realistic simulations.

 

 

Screen Shot 2018-12-12 at 12.04.50.png

 

ExiMotion srl is a start up company created in 2014, and born of the experience and knowledge of the IAS-Lab of University of Padua.

Its main mission is solving the most common problems that arise while using technological devices in the bio-medical field. ExiMotion offers solutions which are highly innovative and with a low cost for the institutions or the final user. Thanks to the scientific/engineering know-how of its team, ExiMotion s.r.l. is bridging the gap between the world of research and that of production. 

EXiMotion s.r.l. has created the Education Department, since it believes that the scientific knowledge is crucial to keep a high quality in the scientific research and in the innovating process, and also for every single nation and Europe in general. The main focus is on Educational Robotics and Creative Coding.

IAS-Lab stands for Intelligent Autonomous Systems Laboratory and it is one of the 28 laboratories of the Department of Information Engineering of the University of Padua.

The activity at IAS-Lab concerns the study of several fields of Robotics. Our research cover the areas of computer vision, humanoids and wheeled robot programming, virtual simulation, biomechanical model based on human biosignal and wearable robots design for rehabilitation purposes.




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