Journal
EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING
Volume -, Issue -, Pages -Publisher
SPRINGEROPEN
DOI: 10.1186/s13638-019-1474-5
Keywords
Path planning; Ant colony algorithm; Grid method; Penalty strategy
Funding
- National key Research and Development Program of China [2017YFB1103603, 2017YFB1103003]
- National Natural Science Foundation of China [61602343, 51607122, 61772365, 41772123, 61802280, 61806143, 61502318]
- Tianjin Province Science and Technology Projects [17JCYBJC15100, 17JCQNJC04500]
- Basic Scientific Research Business Funded Projects of Tianjin [2017KJ093, 2017KJ094]
- Natural Science Foundation of Henan province [182300410286]
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The ant colony optimization algorithm is an effective way to solve the problem of unmanned vehicle path planning. First, establish the environment model of the unmanned vehicle path planning, process and describe the environmental information, and finally realize the division of the problem space. Next, the biomimetic behavior of the ant colony algorithm is described. The ant colony algorithm has been improved by adding a penalty strategy. This penalty strategy can enhance the utilization of resources and guide the ants to explore other unknown areas by using the worse value in the search history to enhance the volatility of the pheromone.
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