Concurrent Map Building and Behavior Learning for Navigation in Unknown Environments
In this paper, we report a robust and low-cost navigation algorithm for an unknown environment based on integration of a grid-based map building algorithm with behavior learning. The study focuses on mobile robots that utilize ultrasonic sensors as their prime interface with the outside
world. The proposed algorithm takes into account environmental information to augment the readings from the low angular accuracy sonar measurements for behavior learning. The environmental information is obtained by an online grid-based map learning design that is concurrently operating with
the behavior learning algorithm. The proposed algorithm is implemented and tested on an in-house-built mobile robot, and its performance is verified through online navigation in an indoor environment.
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GRID-BASED MAP BUILDING
Document Type: Research Article
College of Life Sciences & Technology, HKU SPACE, Hong Kong
School of Engineering Science, Simon Fraser University, 250-13450, 102 Avenue, Surrey, BC V3T 0A3, Canada
Amonics Ltd., Unit 1803-04, Perfect Industrial Building, San Po Kong, Kowloon, Hong Kong
Publication date: 2010-07-01