Learning Flexible and Reusable Locomotion Primitives for a Microrobot

Understand

The design of gaits for robot locomotion can be a daunting process which requires significant expert knowledge and engineering.

• This process is even more challenging for robots that do not have an accurate physical model, such as compliant or micro-scale robots.
• Data-driven gait optimization provides an automated alternative to analytical gait design.
• In this paper, we propose a novel approach to efficiently learn a wide range of locomotion tasks with walking robots.