Computational design towards energy efficient optimization in overconstrained robotic limbs

Yuping Gu, Ziqian Wang, Shihao Feng, Haoran Sun, Haibo Lu, Jia Pan, Fang Wan, Chaoyang Song

Abstract: Legged robots are constantly evolving, and energy efficiency is a major driving factor in their design. However, combining mechanism efficiency and trajectory planning can be challenging. This work proposes a computational optimization framework for optimizing leg design during basic walking while maximizing energy efficiency. We generalize the robotic limb design as a four-bar linkage-based design pool and optimize the leg using an evolutionary algorithm. The leg configuration and design parameters are optimized based on user-defined objective functions. Our framework was validated by comparing it to measured data on our prototype quadruped robot for forward trotting. The Bennett robotic leg was advantageous for omni-directional locomotion with enhanced energy efficiency.