Paper
23 January 2012 Navigating with VFH: a strategy to avoid traps
Chaomin Luo, Mohan Krishnan, Mark Paulik, Utayba Mohammad, Qing Wang
Author Affiliations +
Proceedings Volume 8301, Intelligent Robots and Computer Vision XXIX: Algorithms and Techniques; 830112 (2012) https://doi.org/10.1117/12.912170
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States
Abstract
The IGVC Navigation Challenge course configuration has evolved in complexity to a point where use of a simple reactive local navigation algorithm presents problems in course completion. A commonly used local navigation algorithm, the Vector Field Histogram (VFH), is relatively fast and thus suitable when computational capabilities on a robot are limited. One of the attendant disadvantages of this algorithm is that a robot can get trapped when attempting to get past a concave obstacle structure. The Navigation Challenge course now has several such structures, including some that partially surround waypoints. Elaborate heuristics are needed to make VFH viable in such a situation and their tuning is arduous. An alternate approach that avoids the use of heuristics is to combine a dynamic path planning algorithm with VFH. In this work, the D*Lite path planning algorithm is used to provide VFH with intermediate goals, which the latter then uses as stepping stones to its final destination. Results from simulation studies as well as field deployment are used to illustrate the benefits of using the local navigator in conjunction with a path planner.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chaomin Luo, Mohan Krishnan, Mark Paulik, Utayba Mohammad, and Qing Wang "Navigating with VFH: a strategy to avoid traps", Proc. SPIE 8301, Intelligent Robots and Computer Vision XXIX: Algorithms and Techniques, 830112 (23 January 2012); https://doi.org/10.1117/12.912170
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Cited by 3 scholarly publications.
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KEYWORDS
Mobile robots

Algorithm development

Motion models

Sensors

Computer simulations

Detection and tracking algorithms

Intelligence systems

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