Hashlamon, Iyad and Erbatur, Kemalettin (2013) Ground reaction force sensor fault detection and recovery method based on virtual force sensor for walking biped robots. In: 9th Asian Control Conference (ASCC 2013), Istanbul, Turkey
PDF
06606340.pdf
Download (906kB)
06606340.pdf
Download (906kB)
Official URL: http://dx.doi.org/10.1109/ASCC.2013.6606340
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.
Item Type: | Papers in Conference Proceedings |
---|---|
Uncontrolled Keywords: | Quadratic programming, ground reaction forces , inertial measurement unit (IMU), virtual force sensor, sensor faults |
Divisions: | Faculty of Engineering and Natural Sciences > Academic programs > Mechatronics Faculty of Engineering and Natural Sciences |
Depositing User: | Kemalettin Erbatur |
Date Deposited: | 08 Jan 2014 14:50 |
Last Modified: | 26 Apr 2022 09:14 |
URI: | https://research.sabanciuniv.edu/id/eprint/23697 |