Ground reaction force sensor fault detection and recovery method based on virtual force sensor for walking biped robots

Abstract

This paper presents a novel method for ground force sensor faults detection and faulty signal reconstruction using Virtual force Sensor (VFS) for slow walking bipeds. The design structure of the VFS consists of two steps, the total ground reaction force (GRF) and its location estimation for each leg based on the center of mass (CoM) position, the leg kinematics, and the IMU readings is carried on in the first step. In the second step, the optimal estimation of the distributed reaction forces at the contact points in the feet sole of walking biped is carried on. For the optimal estimation, a constraint model is obtained for the distributed reaction forces at the contact points and the quadratic programming optimization method is used to solve for the GRF. The output of the VFS is used for fault detection and recovery. A faulty signal model is formed to detect the faults based on a threshold, and recover the signal using the VFS outputs. The sensor offset, drift, and frozen output faults are studied and tested. The proposed method detects and estimates the faults and recovers the faulty signal smoothly. The validity of the proposed estimation method was confirmed by simulations on 3D dynamics model of the humanoid robot SURALP while walking. The results are promising and prove themselves well in all of the studied fault cases.Index Terms-Quadratic programming, ground reaction forces, inertial measurement unit (IMU), virtual force sensor, sensor faults.

Optimal gait planning for humanoids with 3D structure walking on slippery surfaces

“…Yamamoto et al used accelerometers on the robot feet to detect slippage of the stance foot. 26 In these research studies, the slippage is detected, only after it occurs. Kaneko et al introduced a slip-observer to detect slippage of the stance foot.…”

“…Hashlamon et al adopted the same approach and developed the Virtual slip Force Sensor (VSFS). 26 In these research studies, the slippage is detected, only after it occurs. However, in order to generate walking patterns consistent with the surface that the robot walks on, the friction coefficient should be estimated before slipping.…”