Imperial College London


Faculty of EngineeringDyson School of Design Engineering




+44 (0)20 7594 9235p.kormushev Website




25 Exhibition Road, 3rd floor, Dyson BuildingDyson BuildingSouth Kensington Campus






BibTex format

author = {AlAttar, A and Rouillard, L and Kormushev, P},
doi = {10.1007/978-3-030-25332-5_31},
publisher = {Springer},
title = {Autonomous air-hockey playing cobot using optimal control and vision-based Bayesian tracking},
url = {},
year = {2019}

RIS format (EndNote, RefMan)

AB - 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.
AU - AlAttar,A
AU - Rouillard,L
AU - Kormushev,P
DO - 10.1007/978-3-030-25332-5_31
PB - Springer
PY - 2019///
SN - 0302-9743
TI - Autonomous air-hockey playing cobot using optimal control and vision-based Bayesian tracking
UR -
UR -
UR -
ER -