A Hybrid Motion Model for Aiding State Estimation in Dynamic Quadrupedal Locomotion

Abstract

Trotting and galloping allow a quadruped to rapidly traverse rough terrain. Modeling this motion, which is only dynamically stable, is of importance for legged robot operation and for quadrupedal animal motion estimation. Derived from an eight-step galloping cycle, this study presents a kinetic hybrid model in which the states vary based on the principal forces present. As compared to foot contact, or kinematic, hybrid quadruped models this reduces the maximum number of possible states from 120 to 6 and provides an alternative to foot contact monitoring. This approach was tested on a trotting quadruped robot equipped with an inertial sensor aided by video. This was processed using an EKF estimator framework to give attitude estimates at rates of up to 250 Hz with 5deg error.