DocumentCode :
3666682
Title :
Slip ratio estimation and control of wheeled mobile robot on different terrains
Author :
Maral Partovibakhsh;Guangjun Liu
Author_Institution :
Department of Aerospace Engineering, Ryerson University, 350 Victoria Street, Toronto, Ontario, Canada
fYear :
2015
fDate :
6/1/2015 12:00:00 AM
Firstpage :
566
Lastpage :
571
Abstract :
This paper presents a model-based algorithm for estimating the longitudinal velocity and online slip ratio control of wheeled mobile robots (WMR). The adaptive unscented Kalman filter (AUKF) is employed to estimate the vehicle longitudinal velocity and the wheel angular velocity in the presence of parameter variations and disturbances using measurements from wheel encoders. An adaptive adjustment of the noise covariances is implemented using a covariance matching technique in the un-scented Kalman filter context for the estimation process. The loss of velocity due to the wheel slip causes extra power consumption. Due to the presence of model uncertainties, parameter variations, and disturbances in the robot nonlinear dynamic system, a sliding mode controller is designed for desired slip control. Experiments are carried out to verify the effectiveness of the estimation algorithm and the controller. In spite of uncertainties presented in the measurements, the robot/wheel dynamics, and terrain condition variations, the controller is able to provide the desired slip ratio control of the mobile robot. It is also demonstrated that the adaptive concept of AUKF leads to better results than the unscented Kalman filter in the robot states estimation which is difficult to measure in practice.
Keywords :
"Wheels","Mobile robots","Kalman filters","Estimation","Robot kinematics","Angular velocity"
Publisher :
ieee
Conference_Titel :
Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), 2015 IEEE International Conference on
Print_ISBN :
978-1-4799-8728-3
Type :
conf
DOI :
10.1109/CYBER.2015.7288002
Filename :
7288002
Link To Document :
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