Active Sensor Fusion for Collision Avoidance in Behaviour-Based Mobile Robots

Terence Chek Hion HENG  Yoshinori KUNO  Yoshiaki SHIRAI  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E81-D   No.5   pp.448-456
Publication Date: 1998/05/25
Online ISSN: 
DOI: 
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Image Processing,Computer Graphics and Pattern Recognition
Keyword: 
mobile robot,  behaviour-based robot,  sonar sensing,  sensor fusion,  active vision,  

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Summary: 
Presently, mobile robots are navigated by means of a number of methods, using navigating systems such as the sonar-sensing system or the visual-sensing system. These systems each have their strengths and weaknesses. For example, although the visual system enables a rich input of data from the surrounding environment, allowing an accurate perception of the area, processing of the images invariably takes time. The sonar system, on the other hand, though quicker in response, is limited in terms of quality, accuracy and range of data. Therefore, any navigation methods that involves only any one system as the primary source for navigation, will result in the incompetency of the robot to navigate efficiently in a foreign, slightly-more-complicated-than-usual surrounding. Of course, this is not acceptable if robots are to work harmoniously with humans in a normal office/laboratory environment. Thus, to fully utilise the strengths of both the sonar and visual sensing systems, this paper proposes a fusion of navigating methods involving both the sonar and visual systems as primary sources to produce a fast, efficient and reliable obstacle-avoiding and navigating system. Furthermore, to further enhance a better perception of the surroundings and to improve the navigation capabilities of the mobile robot, active sensing modules are also included. The result is an active sensor fusion system for the collision avoiding behaviour of mobile robots. This behaviour can then be incorporated into other purposive behaviours (eg. Goal Seeking, Path Finding, etc. ). The validity of this system is also shown in real robot experiments.