Generalized and modified ant algorithm for solving robot path planning problem

The task of planning trajectories for a mobile robot has received considerable attention in the research literature. The problem involves computing a collision-free path between a start point and a target point in environment of known obstacles. In this paper, we introduced the generalized and modif...

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Veröffentlicht in:2010 3rd IEEE International Conference on Computer Science and Information Technology Jg. 1; S. 643 - 646
Hauptverfasser: Maurya, Ritesh, Shukla, Anupam
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.07.2010
Schlagworte:
Adaptation model
Ant colony Optimization
Combinatorial Optimization
Equations
Generalization Levels
Mathematical model
Metaheuristic
Modified ant algorithm
Motion Planning
Planning
Robot Navigation
ISBN:9781424455379, 1424455375
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Abstract The task of planning trajectories for a mobile robot has received considerable attention in the research literature. The problem involves computing a collision-free path between a start point and a target point in environment of known obstacles. In this paper, we introduced the generalized and modified ant algorithm for solving robot path planning, by the term generalized we mean ant can select either one of the 16, 24 or 32 neighbor points for its next movement as contrast to simple one in which only one of the eight neighborhoods can be selected by the ant. As per the general theory of the graph search algorithms, the increase in the number of neighborhood points make the solutions more optimal in terms of path length, but put a limitation on the execution time which increases drastically with an increase in the number of neighborhood points. Our simulation results show that there is a considerable decrease in the path length with the increase in the level of generalization, the time of execution however increases but the algorithm performance can be improved by modified ant algorithm in terms of execution time.
AbstractList The task of planning trajectories for a mobile robot has received considerable attention in the research literature. The problem involves computing a collision-free path between a start point and a target point in environment of known obstacles. In this paper, we introduced the generalized and modified ant algorithm for solving robot path planning, by the term generalized we mean ant can select either one of the 16, 24 or 32 neighbor points for its next movement as contrast to simple one in which only one of the eight neighborhoods can be selected by the ant. As per the general theory of the graph search algorithms, the increase in the number of neighborhood points make the solutions more optimal in terms of path length, but put a limitation on the execution time which increases drastically with an increase in the number of neighborhood points. Our simulation results show that there is a considerable decrease in the path length with the increase in the level of generalization, the time of execution however increases but the algorithm performance can be improved by modified ant algorithm in terms of execution time.
Author Maurya, Ritesh
Shukla, Anupam
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  givenname: Ritesh
  surname: Maurya
  fullname: Maurya, Ritesh
  email: Maurya123ritesh47@gmail.com
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  givenname: Anupam
  surname: Shukla
  fullname: Shukla, Anupam
  email: dranupamshukla@gmail.com
  organization: Dept. of Inf. Technol., ABV-Indian Inst. of Inf., Gwalior, India
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StartPage 643
SubjectTerms Adaptation model
Ant colony Optimization
Combinatorial Optimization
Equations
Generalization Levels
Mathematical model
Metaheuristic
Modified ant algorithm
Motion Planning
Planning
Robot Navigation
Title Generalized and modified ant algorithm for solving robot path planning problem
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