Adaptive genetic algorithm for path planning of loosely coordinated multi-robot manipulators

Sheng Gao; Jie Zhao; He Gao Cai

Adaptive genetic algorithm for path planning of loosely coordinated multi-robot manipulators

Sheng Gao^*
, Jie Zhao
, He Gao Cai

^*Corresponding author for this work

School of Mechatronics Engineering

Harbin Institute of Technology

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

Adaptive genetic algorithm A_SAGA, a novel algorithm, which can dynamically modify the parameters of Genetic Algorithms in terms of simulated annealing mechanism, is proposed for path planning of loosely coordinated multi-robot manipulators. Over the task space of a multi-robot, a strategy of decoupled planning is also applied to be evolutionary process, which enables a multi-robot to avoid falling into deadlock and calculating of composite C-space. Finally, two representative tests are given to validate A_SAGA and the strategy of decoupled planning.

Original language	English
Pages (from-to)	72-76
Number of pages	5
Journal	Journal of Harbin Institute of Technology (New Series)
Volume	10
Issue number	1
State	Published - Mar 2003

Keywords

Adaptive genetic algorithm
Decoupled planning
Multi-robot
Path planning
Simulated annealing

Cite this

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title = "Adaptive genetic algorithm for path planning of loosely coordinated multi-robot manipulators",

abstract = "Adaptive genetic algorithm ASAGA, a novel algorithm, which can dynamically modify the parameters of Genetic Algorithms in terms of simulated annealing mechanism, is proposed for path planning of loosely coordinated multi-robot manipulators. Over the task space of a multi-robot, a strategy of decoupled planning is also applied to be evolutionary process, which enables a multi-robot to avoid falling into deadlock and calculating of composite C-space. Finally, two representative tests are given to validate ASAGA and the strategy of decoupled planning.",

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author = "Sheng Gao and Jie Zhao and Cai, \{He Gao\}",

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AU - Gao, Sheng

AU - Zhao, Jie

AU - Cai, He Gao

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N2 - Adaptive genetic algorithm ASAGA, a novel algorithm, which can dynamically modify the parameters of Genetic Algorithms in terms of simulated annealing mechanism, is proposed for path planning of loosely coordinated multi-robot manipulators. Over the task space of a multi-robot, a strategy of decoupled planning is also applied to be evolutionary process, which enables a multi-robot to avoid falling into deadlock and calculating of composite C-space. Finally, two representative tests are given to validate ASAGA and the strategy of decoupled planning.

AB - Adaptive genetic algorithm ASAGA, a novel algorithm, which can dynamically modify the parameters of Genetic Algorithms in terms of simulated annealing mechanism, is proposed for path planning of loosely coordinated multi-robot manipulators. Over the task space of a multi-robot, a strategy of decoupled planning is also applied to be evolutionary process, which enables a multi-robot to avoid falling into deadlock and calculating of composite C-space. Finally, two representative tests are given to validate ASAGA and the strategy of decoupled planning.

KW - Adaptive genetic algorithm

KW - Decoupled planning

KW - Multi-robot

KW - Path planning

KW - Simulated annealing

UR - https://www.scopus.com/pages/publications/0038785546

M3 - 文章

AN - SCOPUS:0038785546

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JO - Journal of Harbin Institute of Technology (New Series)

JF - Journal of Harbin Institute of Technology (New Series)

IS - 1

ER -

Adaptive genetic algorithm for path planning of loosely coordinated multi-robot manipulators

Abstract

Keywords

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