TL;DR
This paper presents an evolutionary approach to designing embodied phase coordination control systems for quadruped robots, improving real-world robustness and reducing simulation-to-reality performance gaps.
Contribution
It introduces sensor-feedback influenced phase coordination in evolutionary control design, enabling more complex and robust quadruped robot locomotion in real environments.
Findings
Enhanced transferability of control systems from simulation to real robot
Improved robustness in diverse real-world environments
Evolutionary design yields more complex coordination patterns
Abstract
Overcoming robotics challenges in the real world requires resilient control systems capable of handling a multitude of environments and unforeseen events. Evolutionary optimization using simulations is a promising way to automatically design such control systems, however, if the disparity between simulation and the real world becomes too large, the optimization process may result in dysfunctional real-world behaviors. In this paper, we address this challenge by considering embodied phase coordination in the evolutionary optimization of a quadruped robot controller based on central pattern generators. With this method, leg phases, and indirectly also inter-leg coordination, are influenced by sensor feedback.By comparing two very similar control systems we gain insight into how the sensory feedback approach affects the evolved parameters of the control system, and how the performances…
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