Extracting Legged Locomotion Heuristics with Regularized Predictive Control
Gerardo Bledt,Sangbae Kim,Gerardo Bledt,Sangbae Kim
Optimization based predictive control is a powerful tool that has improved the ability of legged robots to execute dynamic maneuvers and traverse increasingly difficult terrains. However, it is often challenging and unintuitive to design meaningful cost functions and build high-fidelity models while adhering to timing restrictions. A novel framework to extract and design principled regularization ...
