Ioannis Havoutis

/Ioannis Havoutis

 

 

Ioannis is a Departmental Lecturer at the Oxford Robotics Institute. His research combines dynamic whole-body motion planning and control with machine learning, focusing on robots with arms and legs.

He received his PhD (2011) and MSc with distinction (2007) from the University of Edinburgh, where he worked on machine learning for motion planning and control of articulated robots.

After his studies, he joined the Dynamic Legged Systems Lab at the Advanced Robotics Department of the Italian Institute of Technology, where he worked on a hydraulically-actuated, fully torque-controlled quadruped robot. There he led the Locomotion Group within the HyQ team, while his work focused on dynamic motionplanning and control for legged locomotion.

He was a postdoctoral researcher at the Robot Learning & Interaction Group of the Idiap Research Institute, where he worked on learning complex skills from demonstration. His work there mainly focused on skill representation, online Bayesian nonparametric learning, Riemannian manifold methods and optimal control for motion generation.

Ioannis’ list of publications can be found here.


2018

  • [PDF] [DOI] I. Havoutis and S. Calinon, “Learning from demonstration for semi-autonomous teleoperation,” Autonomous Robots, 2018.
    [Bibtex]

    @article{2018AuRo_Havoutis,
    author = {Havoutis, Ioannis and Calinon, Sylvain},
    title = {Learning from demonstration for semi-autonomous teleoperation},
    journal = {Autonomous Robots},
    year = {2018},
    month = {Apr},
    day = {25},
    abstract = {Teleoperation in domains such as deep-sea or space often requires the completion of a set of recurrent tasks. We present a framework that uses a probabilistic approach to learn from demonstration models of manipulation tasks. We show how such a framework can be used in an underwater ROV teleoperation context to assist the operator. The learned representation can be used to resolve inconsistencies between the operator's and the robot's space in a structured manner, and as a fall-back system to perform previously learned tasks autonomously when teleoperation is not possible. We evaluate our framework with a realistic ROV task on a teleoperation mock-up with a group of volunteers, showing a significant decrease in time to complete the task when our approach is used. In addition, we illustrate how the system can execute previously learned tasks autonomously when the communication with the operator is lost.},
    issn = {1573-7527},
    doi = {10.1007/s10514-018-9745-2},
    url = {https://doi.org/10.1007/s10514-018-9745-2},
    pdf = {http://www.robots.ox.ac.uk/~mobile/Papers/2018AuRo_Havoutis.pdf},
    }

  • [PDF] [DOI] M. J. A. Zeestraten, I. Havoutis, and S. Calinon, “Programming by Demonstration for Shared Control with an Application in Teleoperation,” IEEE Robotics and Automation Letters (RA-L), 2018.
    [Bibtex]

    @article{Zeestraten17RAL,
    author= {Zeestraten, M. J. A. and Havoutis, I. and Calinon, S.},
    title= {Programming by Demonstration for Shared Control with an Application in Teleoperation},
    journal= {{IEEE} Robotics and Automation Letters ({RA-L})},
    doi= {10.1109/LRA.2018.2805105},
    year= {2018},
    month= {},
    volume= {},
    number= {},
    pages= {},
    pdf= {http://www.robots.ox.ac.uk/~mobile/Papers/2018RAL-Zeestraten.pdf}
    }

2017

  • [PDF] M. J. A. Zeestraten, I. Havoutis, S. Calinon, and D. G. Caldwell, “Learning Task-Space Synergies using Riemannian Geometry,” in Proc. IEEE/RSJ Intl Conf. on Intelligent Robots and Systems (IROS), Vancouver, Canada, 2017.
    [Bibtex]

    @inproceedings{zeestraten2017IROS,
    title = {Learning Task-Space Synergies using Riemannian Geometry},
    author = {Zeestraten, M. J. A. and Havoutis, I. and Calinon, S. and Caldwell, D. G.},
    booktitle = {Proc. {IEEE/RSJ} Intl Conf. on Intelligent Robots and Systems ({IROS})},
    pdf = {http://www.robots.ox.ac.uk/~mobile/Papers/2017IROS_zeestraten.pdf},
    year = {2017},
    address = {Vancouver, Canada},
    month = {October}
    }

  • [PDF] C. Mastalli, M. Focchi, I. Havoutis, A. Radulescu, S. Calinon, J. Buchli, D. G. Caldwell, and C. Semini, “Trajectory and Foothold Optimization using Low-Dimensional Models for Rough Terrain Locomotion,” in IEEE Intl. Conf. on Robotics and Automation (ICRA), Singapore, 2017.
    [Bibtex]

    @ inproceedings{2017icra_mastalli,
    author = {Carlos Mastalli and Michelle Focchi and Ioannis Havoutis and Andreea Radulescu and Sylvain Calinon and Jonas Buchli and Darwin G. Caldwell and Claudio Semini},
    title = {Trajectory and Foothold Optimization using Low-Dimensional Models for Rough Terrain Locomotion},
    booktitle = {IEEE Intl. Conf. on Robotics and Automation (ICRA)},
    year = 2017,
    address = {Singapore},
    month = may,
    pdf = {http://www.robots.ox.ac.uk/~mobile/Papers/2017ICRA_mastalli.pdf}
    }

  • [PDF] A. Radulescu, I. Havoutis, D. G. Caldwell, and C. Semini, “Whole-body Trajectory Optimization for Non-periodic Dynamic Motions on Quadrupedal Systems,” in IEEE Intl. Conf. on Robotics and Automation (ICRA), Singapore, 2017.
    [Bibtex]

    @inproceedings{2017icra_radulescu,
    author = {Andreea Radulescu and Ioannis Havoutis and Darwin G. Caldwell and Claudio Semini},
    title = {Whole-body Trajectory Optimization for Non-periodic Dynamic Motions on Quadrupedal Systems},
    booktitle = {IEEE Intl. Conf. on Robotics and Automation (ICRA)},
    year = 2017,
    address = {Singapore},
    month = may,
    pdf = {http://www.robots.ox.ac.uk/~mobile/Papers/2017ICRA_radulescu.pdf}
    }

  • [PDF] [DOI] M. J. A. Zeestraten, I. Havoutis, J. Silvério, S. Calinon, and D. G. Caldwell, “An Approach for Imitation Learning on Riemannian Manifolds,” IEEE Robotics and Automation Letters (RA-L), vol. 2, iss. 3, pp. 1240-1247, 2017.
    [Bibtex]

    @article{Zeestraten17RAL,
    author=  {Zeestraten, M. J. A. and Havoutis, I. and Silv\'erio, J. and Calinon, S. and Caldwell, D. G.},
    title=  {An Approach for Imitation Learning on {R}iemannian Manifolds},
    journal=  {{IEEE} Robotics and Automation Letters ({RA-L})},
    doi= {10.1109/LRA.2017.2657001},
    year= {2017},
    month=  {June},
    volume=  {2},
    number=  {3},
    pages=  {1240--1247},
    pdf= {http://www.robots.ox.ac.uk/~mobile/Papers/2017RAL_zeestraten.pdf}
    }

  • [PDF] I. Havoutis and S. Calinon, “Supervisory teleoperation with online learning and optimal control,” in Proc. IEEE Intl Conf. on Robotics and Automation (ICRA), Singapore, 2017.
    [Bibtex]

    @inproceedings{Havoutis17ICRA,
    author =  {Havoutis, I. and Calinon, S.},
    title = {Supervisory teleoperation with online learning and optimal control},
    booktitle =  {Proc. {IEEE} Intl Conf. on Robotics and Automation ({ICRA})},
    year =  {2017},
    month =  {May-June},
    address =  {Singapore},
    pages =  {},
    pdf = {http://www.robots.ox.ac.uk/~mobile/Papers/2017ICRA_havoutis.pdf}
    }




2017-10-14T12:59:42+00:00