Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
Genetic and evolutionary algorithms come of age
Communications of the ACM
Artificial Intelligence: A Guide to Intelligent Systems
Artificial Intelligence: A Guide to Intelligent Systems
A Unified Approach to Planning, Sensing and Navigation for Mobile Robots
The 3rd International Symposium on Experimental Robotics III
Genetic Algorithms for Adaptive Motion Planning of an Autonomous Mobile Robot
CIRA '97 Proceedings of the 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation
Ant Colony Optimization
The Ant Algorithm for Solving Robot Path Planning Problem
ICITA '05 Proceedings of the Third International Conference on Information Technology and Applications (ICITA'05) Volume 2 - Volume 02
Introduction to Genetic Algorithms
Introduction to Genetic Algorithms
Ant colony system for robot path planning in global static environment
ICOSSSE'10 Proceedings of the 9th WSEAS international conference on System science and simulation in engineering
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This paper presents the application of Genetic Algorithm (GA) and Ant Colony Optimization (ACO) Algorithm for robot path planning (RPP) in global static environment. Both algorithms were applied within global maps that consist of different number of free space nodes. These nodes generally represent the free space extracted from the robot map. Performances between both algorithms were compared and evaluated in terms of speed and number of iterations that each algorithm takes to find an optimal path within several selected environments. The effectiveness and efficiency of both algorithms were tested using a simulation approach. Comparison of the performances and parameter settings, advantages and limitations of both algorithms presented herewith can be used to further expand the optimization algorithm in RPP research area.