Hardware design of autonomous snake-like robot for reinforcement learning based on environment: discussion of versatility on different tasks

Abstract

In this paper, we propose the design of a robot with a snake-like body based on a test environment. We explore the abstraction of state-action spaces for reinforcement learning. Additionally, we discuss the versatility of the proposed mechanism by showing that different tasks can be completed by simply changing the reward of the reinforcement learning. Finally, we mention the importance of a body design based on an environment by considering the concept of ecological niches.