Model-Free Self-Calibration of Force-Sensing Shoes for Humanoids
Abstract
This paper presents a novel model-free method for humanoid robot quasi-static movement control to self-calibrate their foot force sensor. Traditional model-based methods typically rely on accurate robot model parameters, including kinematic and inertial parameters, to generate whole-body trajectories. In contrast, we propose a proprioceptive framework based only on sensory outputs. Our model-free whole-body trajectory planner consists of three steps:1. Planning different pairs of the center of pressure (CoP) and foot position objectives. 2. Searching around the current configuration by slightly moving the robot’s leg joints back and forth while recording the sensor measurements of its CoP and foot positions. 3. Updating the robot motion with an optimization algorithm until all objectives are achieved. Then, the foot sensor parameters are determined by minimizing the error between the measured and reference CoP and ground reaction force (GRF) during the robot’s movement using optimization. We demonstrate our approach on a NAO humanoid robot platform. Experiment results show that the model-free self-calibration can successfully estimate CoP and GRF.
