Recommended Citation
Published in 2010 International Conference On Computer Design and Applications, Volume 3, June 25, 2010, pages 436-440.
The definitive version is available at https://doi.org/10.1109/ICCDA.2010.5541300.
Abstract
Path planning is an essential task for the navigation and motion control of autonomous robot manipulators. This NP-complete problem is difficult to solve, especially in a dynamic environment where the optimal path needs to be rerouted in real-time when a new obstacle appears. The ACO (Ant Colony Optimization) algorithm is an optimization technique based on swarm intelligence. This paper investigates the application of ACO to robot path planning in a dynamic environment. Two different pheromone re-initialization schemes are compared and computer simulation results are presented.
Disciplines
Electrical and Computer Engineering
Copyright
2010 IEEE.
Publisher statement
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URL: https://digitalcommons.calpoly.edu/eeng_fac/205