Joint sensor fault detection and recovery based on virtual sensor for walking legged robots

Warning The system is temporarily closed to updates for reporting purpose.

Hashlamon, Iyad and Erbatur, Kemalettin (2014) Joint sensor fault detection and recovery based on virtual sensor for walking legged robots. In: IEEE 23rd International Symposium on Industrial Electronics (ISIE 2014), Istanbul, Turkey

Full text not available from this repository. (Request a copy)

Abstract

This paper presents a novel method for joint sensor faults detection and faulty signal reconstruction. It uses the Virtual Joint Sensor (VJS). The model structure of the VJS consists of two interconnected models: The simple Linear Inverted Pendulum Model (LIPM) and the robot leg kinematics model (LKM). Kalman filter based on LIPM estimates the Center of Mass (CoM) position of the biped. The LKM uses the estimated CoM position to calculate the joints angles. A faulty signal model is formed to detect the faults, based on an adaptive threshold, and recovers the signal using the VJS outputs. The sensor abrupt, incipient, and frozen output faults are studied and tested. The validity of the proposed method was confirmed by simulations on 3D dynamics model of the humanoid robot SURALP while walking on a flat terrain.
Item Type: Papers in Conference Proceedings
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Mechatronics
Faculty of Engineering and Natural Sciences
Depositing User: Kemalettin Erbatur
Date Deposited: 14 Dec 2014 22:15
Last Modified: 26 Apr 2022 09:17
URI: https://research.sabanciuniv.edu/id/eprint/25786

Actions (login required)

View Item
View Item