Inertial Human Motion Estimation for Physical Human-Robot Interaction Using an Interaction Velocity Update to Reduce Drift

Abstract

Robots used for physical human-robot interaction (pHRI) are currently advancing from being simple stand-alone manipulators passing tools or parts to human collaborators to becoming autonomous co-workers that continuously share operational control with their human partners. One of the major challenges in this transition is to extend robot capabilities in sensing human motions and behaviour, thereby allowing for more seamless cooperation and ensuring the safety of human partners. Currently, there is a gap between the desire for humans and robots to work closely together and share control of operations, and how robustly we can measure and predict human motions and intentions in pHRI operations. In this paper, we propose to use a set of wireless inertial motion sensors fixed to the body of the human partner to track and estimate human motions, and to use the interaction contact between the robot and the human, as detected by a force/torque (FT) sensor, as an interaction velocity update (IVU) to estimate and reduce drift in the position/orientation estimates. Our hypothesis is that human motion estimates from inertial sensors with an IVU will give sufficiently accurate and robust motion information for safe cooperative pHRI operations.