NDLI: An adaptive roadmap guided Multi-RRTs strategy for single query path planning

Content Provider	IEEE Xplore Digital Library
Author	Wei Wang Yan Li Xin Xu Yang, S.X.
Copyright Year	2010
Description	Author affiliation: College of Mechatronics and Automation, National University of Defense Technology, Changsha, 410073, China (Wei Wang; Yan Li; Xin Xu) \|\| ARIS Lab, School of Engineering, University of Guelph, Canada (Yang, S.X.)
Abstract	During the past decade, Rapidly-exploring Random Tree (RRT) and its variants are shown to be powerful sampling based single query path planning approaches for robots in high-dimensional configuration space. However, the performance of such tree-based planners that rely on uniform sampling strategy degrades significantly when narrow passages are contained in the configuration space. Given the assumption that computation resources should be allocated in proportion the geometric complexity of local region, we present a novel single-query Multi-RRTs path planning framework that employs an improved Bridge Test algorithm to identify global important roadmaps in narrow passages. Multiple trees can grown from these sampled roadmaps to explore sub-regions which are difficult to reach. The probability of selecting one particular tree for expansion and connection, which can dynamically updated by on-line learning algorithm based on the historic results of exploration, guides the tree through narrow passage rapidly. Experimental results show that the proposed approach gives substantial improvement in planning efficiency over a wide range of single-query path planning problems.
Starting Page	2871
Ending Page	2876
File Size	414952
Page Count	6
File Format	PDF
ISBN	9781424450381
ISSN	10504729
DOI	10.1109/ROBOT.2010.5509529
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-05-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Path planning Sampling methods Orbital robotics Motion planning Resource management Robots Space exploration Robotics and automation USA Councils Strategic planning
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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