Online Determination of Legged Kinematics

Abstract

Legged robots are emerging, and legged locomotion is in critical need, which requires precise leg-body kinematics to execute control commands or plan motion trajectories. This paper proposes online state estimation to determine legged kinematics of robots with an arbitrary number of legs, which includes the kinematic parameters of the leg-body transformation, time offset and the leg link lengths. In particular, we advocate an in-place dance gait for kinematic determination where the toes remain static on the ground and serve as static landmarks as in SLAM. As a visual-inertial sensor is typically available onboard robot and located at the floating base, we leverage efficient MSCKF-based visual-inertial navigation to estimate legged kinematics. To this end, we analytically derive the legged kinematic measurements and tightly fuse them along with visual-inertial measurements for MSCKF update of both the leg’s kinematics and body’s motion. The proposed method has been extensively validated in both simulations and experiments with different quadrupeds, showing its robustness and accuracy.