NDLI: Hybrid probabilistic RoadMap - Monte Carlo motion planning for closed chain systems with spherical joints

Content Provider	IEEE Xplore Digital Library
Author	Li Han
Copyright Year	2004
Description	Author affiliation: Dept. of Math. & Comput. Eng., Clark Univ., Worcester, MA, USA (Li Han)
Abstract	We propose a hybrid probabilistic RoadMap - Monte Carlo (PRM-MC) motion planner developed under the general methodology of PRM. For a given robot, PRM planners generally need to sample and connect a large number of robot configurations in order to build a roadmap that reflects the properties (such as the connectivity or energy landscape) of the robot configuration space. The proposed PRM-MC planner uses Monte Carlo simulation to generate and connect neighboring robot configurations and uses PRM local planners to connect the connected components generated from MC simulation. This strategy follows the random sampling principle of PRM that leads to the probabilistic completeness of the PRM-type randomized planners, while exploring the continuity property of motion planning constraints to improve the computation efficiency and roadmap quality. We apply the PRM-MC approach to closed chain motion planning In this work. Our current planner uses rotation pivots as attempted Monte Carlo moves for 3D closed chains with spherical joints. Pivot motions are developed as an efficient way to deform closed chains without violating the closure constraints, which have proved problematical for randomized approaches. We discuss how to identify feasible rotation pivots of kinematic chains and utilize them in PRM-MC planning. Our simulation results show that the PRM-MC closed chain planner can build road maps with good connectivity and efficiently generate self-collision-free closure configurations for closed chain systems with many links and multiple loops.
Sponsorship	IEEE Robotics and Automation Soc
Starting Page	920
Ending Page	926
File Size	628219
Page Count	7
File Format	PDF
ISBN	0780382323
ISSN	10504729
DOI	10.1109/ROBOT.2004.1307267
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-04-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Monte Carlo methods Motion planning Orbital robotics Robot motion Sampling methods Path planning Road accidents Mathematics Computer science Computational modeling
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software

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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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