Anytime ant system for manipulator path planning

D. Wang; N. M. Kwok; G. Fang; Q. P. Ha

doi:10.1007/978-3-642-19959-2_50

Anytime ant system for manipulator path planning

D. Wang, N. M. Kwok, G. Fang, Q. P. Ha

Research output: Chapter in Book / Conference Paper › Chapter

Abstract

An efficient algorithm for manipulator path planning is presented in this paper. Because of the complexity of the problem nature, it frequently takes a long time for the planner to find an optimal path. This drawback may hinder a robotic manipulator system from many real-time applications. In this research work, the concept of anytime algorithm is integrated into a novel swarm intelligence method, the Ant System with Negative Feedback (ASNF). With the proposed Anytime Ant System (AAS), a planner is able to find a suboptimal solution quickly, then improve the quality of this solution while time allows. Simulations based on a two-link manipulator have been carried out to demonstrate the feasibility and effectiveness of the proposed approach.

Original language	English
Title of host publication	Robotic Welding, Intelligence and Automation RWIA'2010
Editors	Tzyh-Jong Tarn, Shan-Ben Chen, Gu Fang
Place of Publication	Germany
Publisher	Springer
Pages	411-420
Number of pages	10
ISBN (Electronic)	9783642199592
ISBN (Print)	9783642199585
DOIs	https://doi.org/10.1007/978-3-642-19959-2_50
Publication status	Published - 2011

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10.1007/978-3-642-19959-2_50

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title = "Anytime ant system for manipulator path planning",

abstract = "An efficient algorithm for manipulator path planning is presented in this paper. Because of the complexity of the problem nature, it frequently takes a long time for the planner to find an optimal path. This drawback may hinder a robotic manipulator system from many real-time applications. In this research work, the concept of anytime algorithm is integrated into a novel swarm intelligence method, the Ant System with Negative Feedback (ASNF). With the proposed Anytime Ant System (AAS), a planner is able to find a suboptimal solution quickly, then improve the quality of this solution while time allows. Simulations based on a two-link manipulator have been carried out to demonstrate the feasibility and effectiveness of the proposed approach.",

author = "D. Wang and Kwok, {N. M.} and G. Fang and Ha, {Q. P.}",

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TY - CHAP

T1 - Anytime ant system for manipulator path planning

AU - Wang, D.

AU - Kwok, N. M.

AU - Fang, G.

AU - Ha, Q. P.

PY - 2011

Y1 - 2011

N2 - An efficient algorithm for manipulator path planning is presented in this paper. Because of the complexity of the problem nature, it frequently takes a long time for the planner to find an optimal path. This drawback may hinder a robotic manipulator system from many real-time applications. In this research work, the concept of anytime algorithm is integrated into a novel swarm intelligence method, the Ant System with Negative Feedback (ASNF). With the proposed Anytime Ant System (AAS), a planner is able to find a suboptimal solution quickly, then improve the quality of this solution while time allows. Simulations based on a two-link manipulator have been carried out to demonstrate the feasibility and effectiveness of the proposed approach.

AB - An efficient algorithm for manipulator path planning is presented in this paper. Because of the complexity of the problem nature, it frequently takes a long time for the planner to find an optimal path. This drawback may hinder a robotic manipulator system from many real-time applications. In this research work, the concept of anytime algorithm is integrated into a novel swarm intelligence method, the Ant System with Negative Feedback (ASNF). With the proposed Anytime Ant System (AAS), a planner is able to find a suboptimal solution quickly, then improve the quality of this solution while time allows. Simulations based on a two-link manipulator have been carried out to demonstrate the feasibility and effectiveness of the proposed approach.

UR - http://handle.uws.edu.au:8081/1959.7/543522

U2 - 10.1007/978-3-642-19959-2_50

DO - 10.1007/978-3-642-19959-2_50

M3 - Chapter

SN - 9783642199585

SP - 411

EP - 420

BT - Robotic Welding, Intelligence and Automation RWIA'2010

A2 - Tarn, Tzyh-Jong

A2 - Chen, Shan-Ben

A2 - Fang, Gu

PB - Springer

CY - Germany

ER -

Anytime ant system for manipulator path planning

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