Reinforcement Learning Methods in Robotic Fish: Survey

Abstract

Reinforcement learning control has gained increasing attention in the field of biomimetic robotic fish, due to its advantage of universal applicability without prior knowledge of dynamic modeling. In this paper, we review the research work on the application of reinforcement learning in the field of robotic fish. We present and discuss the general model of applying reinforcement learning approaches to robotic fish control, such as the design of environment, state, reward and the selection of reinforcement learning algorithm. Furthermore, we propose to divide the typical tasks of reinforcement learning applied in robotic fish into single control and swarm control, and review the recent advancements separately.