Ant Colony Optimization Based on Maximum Selection Probability for Path Planning in Unknown Environment

Provided by: Chongqing University
Topic: Security
Format: PDF
To increase efficiency of global convergence and prevent premature stagnation in path planning of multiple mobile agents, an Ant Colony Optimization based on Maximum Selection Probability (ACOMSP) is proposed. In the process of environmental modeling, grid method is adopted to simplify the environment, and heuristic information is connected with simplified environment. The mechanism of choosing next node is improved and this modified algorithm is applied to path planning of multiple mobile agents. Experiment results show that compared with self-adaptive ant colony algorithm for path planning in unknown environment, the proposed algorithm greatly cuts the search time, reduces space complexity and improves convergent performance.

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