FPGA implementation of improved ant colony optimization algorithm for path planning

Chen Chien Hsu, Wei Yen Wang, Yi Hsing Chien, Ru Yu Hou, Chin Wang Tao

研究成果: 書貢獻/報告類型會議論文篇章

7 引文 斯高帕斯(Scopus)

摘要

An improved ant colony optimization (ACO) algorithm is proposed in this paper for improving the accuracy of path planning. The main idea of this paper is to avoid local minima by continuously tuning a setting parameter and the establishment of novel mechanisms for updating partial pheromone and opposite pheromone. As a result, the global search of the proposed ACO algorithm can be significantly enhanced in terms of calculating optimal path compared to the conventional ACO algorithm. Simulation results of the proposed approach show better performances in terms of the shortest distance, mean distance, and success rate towards optimal paths. To further reduce the computation time, the proposed ACO algorithm for path planning is realized on a FPGA chip to verify its practicalities. Experimental results indicate that the efficiency of the path planning is significantly improved by the hardware design of embedded applications.

原文英語
主出版物標題2016 IEEE Congress on Evolutionary Computation, CEC 2016
發行者Institute of Electrical and Electronics Engineers Inc.
頁面4516-4521
頁數6
ISBN(電子)9781509006229
DOIs
出版狀態已發佈 - 2016 十一月 14
事件2016 IEEE Congress on Evolutionary Computation, CEC 2016 - Vancouver, 加拿大
持續時間: 2016 七月 242016 七月 29

出版系列

名字2016 IEEE Congress on Evolutionary Computation, CEC 2016

其他

其他2016 IEEE Congress on Evolutionary Computation, CEC 2016
國家/地區加拿大
城市Vancouver
期間2016/07/242016/07/29

ASJC Scopus subject areas

  • 人工智慧
  • 建模與模擬
  • 電腦科學應用
  • 控制和優化

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