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
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.