Articulated robot motion planning using ant colony optimisation

Mohd Murtadha Mohamad; Nicholas K. Taylor; Mathew Walter Dunnigan

doi:10.1109/IS.2006.348503

Articulated robot motion planning using ant colony optimisation

Mohd Murtadha Mohamad, Nicholas K. Taylor, Mathew Walter Dunnigan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

17 Citations (Scopus)

Abstract

A new approach to robot motion planning is proposed by applying Ant Colony Optimization (ACO) with the probabilistic roadmap planner (PRM). The aim of this approach is to apply ACO to 3-dimensional robot motion planning which is complicated when involving mobile 6-dof or multiple articulated robots. An ant colony robot motion planning (ACRMP) method is proposed that has the benefit of collective behaviour of ants foraging from a nest to a food source. A number of artificial ants are released from the nest (start configuration) and begin to forage (search) towards the food (goal configuration). During the foraging process, a 1-TREE (uni-directional) searching strategy is applied in order to establish any possible connection from the nest to goal. Results from preliminary tests show that the ACRMP is capable of reducing the intermediate configuration between the initial and goal configuration in an acceptable running time.

Original language	English
Title of host publication	2006 3rd International IEEE Conference Intelligent Systems, Vols 1 and 2
Place of Publication	NEW YORK
Publisher	IEEE
Pages	690-695
Number of pages	6
ISBN (Print)	1424401968, 9781424401963
DOIs	https://doi.org/10.1109/IS.2006.348503
Publication status	Published - 2006
Event	3rd IEEE International Conference on Intelligent Systems - London Duration: 4 Sept 2006 → 6 Sept 2006

Conference

Conference	3rd IEEE International Conference on Intelligent Systems
City	London
Period	4/09/06 → 6/09/06

Keywords

Ant colony
Robot path planning
Search technique

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10.1109/IS.2006.348503

Cite this

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title = "Articulated robot motion planning using ant colony optimisation",

abstract = "A new approach to robot motion planning is proposed by applying Ant Colony Optimization (ACO) with the probabilistic roadmap planner (PRM). The aim of this approach is to apply ACO to 3-dimensional robot motion planning which is complicated when involving mobile 6-dof or multiple articulated robots. An ant colony robot motion planning (ACRMP) method is proposed that has the benefit of collective behaviour of ants foraging from a nest to a food source. A number of artificial ants are released from the nest (start configuration) and begin to forage (search) towards the food (goal configuration). During the foraging process, a 1-TREE (uni-directional) searching strategy is applied in order to establish any possible connection from the nest to goal. Results from preliminary tests show that the ACRMP is capable of reducing the intermediate configuration between the initial and goal configuration in an acceptable running time.",

keywords = "Ant colony, Robot path planning, Search technique",

author = "Mohamad, {Mohd Murtadha} and Taylor, {Nicholas K.} and Dunnigan, {Mathew Walter}",

year = "2006",

doi = "10.1109/IS.2006.348503",

language = "English",

isbn = "1424401968",

pages = "690--695",

booktitle = "2006 3rd International IEEE Conference Intelligent Systems, Vols 1 and 2",

publisher = "IEEE",

address = "United States",

note = "3rd IEEE International Conference on Intelligent Systems ; Conference date: 04-09-2006 Through 06-09-2006",

}

TY - GEN

T1 - Articulated robot motion planning using ant colony optimisation

AU - Mohamad, Mohd Murtadha

AU - Taylor, Nicholas K.

AU - Dunnigan, Mathew Walter

PY - 2006

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N2 - A new approach to robot motion planning is proposed by applying Ant Colony Optimization (ACO) with the probabilistic roadmap planner (PRM). The aim of this approach is to apply ACO to 3-dimensional robot motion planning which is complicated when involving mobile 6-dof or multiple articulated robots. An ant colony robot motion planning (ACRMP) method is proposed that has the benefit of collective behaviour of ants foraging from a nest to a food source. A number of artificial ants are released from the nest (start configuration) and begin to forage (search) towards the food (goal configuration). During the foraging process, a 1-TREE (uni-directional) searching strategy is applied in order to establish any possible connection from the nest to goal. Results from preliminary tests show that the ACRMP is capable of reducing the intermediate configuration between the initial and goal configuration in an acceptable running time.

AB - A new approach to robot motion planning is proposed by applying Ant Colony Optimization (ACO) with the probabilistic roadmap planner (PRM). The aim of this approach is to apply ACO to 3-dimensional robot motion planning which is complicated when involving mobile 6-dof or multiple articulated robots. An ant colony robot motion planning (ACRMP) method is proposed that has the benefit of collective behaviour of ants foraging from a nest to a food source. A number of artificial ants are released from the nest (start configuration) and begin to forage (search) towards the food (goal configuration). During the foraging process, a 1-TREE (uni-directional) searching strategy is applied in order to establish any possible connection from the nest to goal. Results from preliminary tests show that the ACRMP is capable of reducing the intermediate configuration between the initial and goal configuration in an acceptable running time.

KW - Ant colony

KW - Robot path planning

KW - Search technique

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U2 - 10.1109/IS.2006.348503

DO - 10.1109/IS.2006.348503

M3 - Conference contribution

SN - 1424401968

SN - 9781424401963

SP - 690

EP - 695

BT - 2006 3rd International IEEE Conference Intelligent Systems, Vols 1 and 2

PB - IEEE

CY - NEW YORK

T2 - 3rd IEEE International Conference on Intelligent Systems

Y2 - 4 September 2006 through 6 September 2006

ER -

Articulated robot motion planning using ant colony optimisation

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