Fusion of force-torque sensors, inertial measurements units and proprioception for a humanoid kinematics-dynamics observation

Abstract

We present a scheme where the measurements obtained through inertial measurement units (IMU), contact-force sensors and proprioception (joint encoders) are merged in order to observe humanoid unactuated floating-base dynamics. The sensor data fusion is implemented using an Extended Kalman Filter. The prediction part is constituted by viscoelastic contacts assumption and a model expressing at the origin the full body dynamics. The correction is achieved using embedded IMU and force sensor. Simulation and experimentation on HRP-2 robot show a state observation with improves inter-sensor consistency but also increased reconstruction accuracy.