Title :
Joint sensor fault detection and recovery based on virtual sensor for walking legged robots
Author :
Hashlamon, I. ; Erbatur, K.
Author_Institution :
Fac. of Eng. & Natural Sci., Sabanci Univ., Istanbul, Turkey
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.
Keywords :
Kalman filters; fault diagnosis; gait analysis; humanoid robots; linear systems; mobile robots; nonlinear systems; pendulums; robot kinematics; sensors; signal reconstruction; 3D dynamics model; CoM position estimation; Kalman filter; LIPM; LKM; VJS; adaptive threshold; center of mass position estimation; faulty signal reconstruction; humanoid robot SURALP; joint sensor fault detection; joint sensor fault recovery; joints angle calculation; linear inverted pendulum model; robot leg kinematics model; signal recovery; virtual joint sensor; walking legged robot; Fault detection; Joints; Kalman filters; Kinematics; Legged locomotion; Robot sensing systems; Kalman filter; Sensor faults; ZMP; fault detection; inertial measurement unit (IMU); virtual sensor;
Conference_Titel :
Industrial Electronics (ISIE), 2014 IEEE 23rd International Symposium on
Conference_Location :
Istanbul
DOI :
10.1109/ISIE.2014.6864786
