Rapid Bipedal Gait Optimization in CasADi

Abstract

This paper shows how CasADi’s state-of-the-art implementation of algorithmic differentiation can be leveraged to formulate and efficiently solve gait optimization problems, enabling rapid gait design for high-dimensional biped robots. Comparative studies on a 7-DOF planar biped show that CasADi generates optimal gaits 4 times faster than another existing advanced optimization package. The framework is also applied to simultaneously generate a gait and a feedback controller for 2 spatial bipeds: a 12-DOF model and a 20DOF model. Results suggest that CasADi’s unprecedented efficiency could provide a practical path toward real-time gait optimization for high-dimensional biped robots.