A distributed MEMS gyro network for joint velocity estimation

Abstract

This paper is about improving joint and actuator velocity estimates on a human-sized hydraulic humanoid robot by adding a network of inexpensive microelectromechanical systems (MEMS) gyroscopes. Due to the lack of joint velocity sensors on the majority of humanoid robots, the joint velocity estimates often become a limiting factor on the controller performance. The distributed gyroscopes serve as indirect sensors of the joint velocities that can be estimated by a Kalman filter. Using this framework, we achieve higher velocity gains at the center of mass level on an Atlas hydraulic humanoid robot, which translates into better control performance.