Improved Ant Colony Algorithm Based on Forest Comprehensive Cost Map and Research-optimization Mechanism
An improved ant colony algorithm based on the comprehensive cost map of forest land and the research-optimization mechanism is proposed to address the problem of the traditional ant colony algorithms which is absent of considerationof forest terrain and surface conditions in forestry robot path planning,slow at convergence speed and prone to falling into local optima.On the terrain and surface of the forest area,a comprehensive forest land cost map is constructed;a pioneering optimization mechanism is introduced in the ant colony search stage;and a random walk mechanism is led into the roulette wheel mechanism,which is applied the path planning problem of forestry robots.The experiments show that the proposed algorithm proposed can search for better paths and has better exploration and optimization capabilities.
ant colonyelite rewardsdouble layer ant colony algorithmforest path planning
国家科技期刊平台
NSTL
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