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Autonomous Air-Hockey Playing Cobot Using Optimal Control and Vision-Based Bayesian Tracking

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Towards Autonomous Robotic Systems (TAROS 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11650))

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Abstract

This paper presents a novel autonomous air-hockey playing collaborative robot (cobot) that provides human-like gameplay against human opponents. Vision-based Bayesian tracking of the puck and striker are used in an Analytic Hierarchy Process (AHP)-based probabilistic tactical layer for high-speed perception. The tactical layer provides commands for an active control layer that controls the Cartesian position and yaw angle of a custom end effector. The active layer uses optimal control of the cobot’s posture inside the task nullspace. The kinematic redundancy is resolved using a weighted Moore-Penrose pseudo-inversion technique. Experiments with human players show high-speed human-like gameplay with potential applications in the growing field of entertainment robotics.

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Notes

  1. 1.

    A video demonstration of the system is available at: https://www.imperial.ac.uk/robot-intelligence/videos/.

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Author information

Authors and Affiliations

  1. Robot Intelligence Lab, Imperial College London, London, UK

    Ahmad AlAttar, Louis Rouillard & Petar Kormushev

Authors
  1. Ahmad AlAttar
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  2. Louis Rouillard
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  3. Petar Kormushev
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Corresponding author

Correspondence to Ahmad AlAttar .

Editor information

Editors and Affiliations

  1. Queen Mary University of London, London, UK

    Kaspar Althoefer

  2. Queen Mary University of London, London, UK

    Jelizaveta Konstantinova

  3. Queen Mary University of London, London, UK

    Ketao Zhang

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AlAttar, A., Rouillard, L., Kormushev, P. (2019). Autonomous Air-Hockey Playing Cobot Using Optimal Control and Vision-Based Bayesian Tracking. In: Althoefer, K., Konstantinova, J., Zhang, K. (eds) Towards Autonomous Robotic Systems. TAROS 2019. Lecture Notes in Computer Science(), vol 11650. Springer, Cham. https://doi.org/10.1007/978-3-030-25332-5_31

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  • DOI: https://doi.org/10.1007/978-3-030-25332-5_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-25331-8

  • Online ISBN: 978-3-030-25332-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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