Real-time motion planning of an autonomous mobile manipulator using a fuzzy adaptive Kalman filter

Authors:
Homayoun Najjaran;Andrew Goldenberg
Affiliations:
School of Engineering, University of British Columbia Okanagan, Kelowna, BC V1V 1V7, Canada;Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON M5S 3G8, Canada
Venue:
Robotics and Autonomous Systems
Year:
2007

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Abstract

This paper presents the real-time motion planning i.e., map building and path planning of an autonomous mobile manipulator capable of scanning natural terrain using a detector e.g., a landmine detector. Map building generates a terrain map using the measurements of laser and ultrasonic rangefinders, and path planning uses the map to define an obstacle-free path for the detector. Map building involves sensor fusion to tackle the uncertainties associated with range measurement. Fusion takes place in a hierarchical filtering process that updates the map in real time and also optimizes the scanning process based on the terrain type. The filtering process includes a proposed fuzzy adaptive Kalman filter in which the gain of the filter is adapted using a fuzzy model that characterizes the terrain. The efficiency of the proposed map building and path planning methods has been verified by experiments on a prototype mine detector robot.