Model-free and model-based time-optimal control of a badminton robot

M. Liu, B. Depraetere, G. Pinte, I. Grondman, R. Babuska
2013 2013 9th Asian Control Conference (ASCC)  
In this research, time optimal control is considered for the hit motion of a badminton robot during a serve operation. For this task the racket always starts at rest in a given position and has to move to a target state, defined by a target position and a non-zero target velocity. The goal is to complete these motions in as little time as possible, yet without violating bounds on the actuator. To find controllers satisfying these requirements, a reinforcement learning approach has been
more » ... ed, using a Natural Actor-Critic (NAC) reinforcement learning algorithm. This approach is experimentally shown to yield the desired robot motions after about 200 trials. Next to this model-free learning approach, a model-based optimization is also calculated numerically and the obtained control signals are applied to the robot. The results achieved with the two approaches are compared, and a thorough analysis is presented, highlighting the properties of each approach, as well as their advantages and drawbacks.
doi:10.1109/ascc.2013.6606242 dblp:conf/ascc/LiuDPGB13 fatcat:f33ygorfqnc4lmxiazpn4kzcqm