Mobile Robot Path Planning based on Parameter Optimization Ant Colony Algorithm

摘要

The basic ant colony algorithm for mobile robot path planning exists many problems, such as lack of stability, algorithm premature convergence, more difficult to find optimal solution for complex problems and so on. This paper proposes improvement measures. Apply genetic algorithm to optimization and configuration parameters of the basic ant colony algorithm. Simulation results show that the improved optimal path length significantly less than the basic ant colony algorithm and volatility is smaller, stability significantly improves. The stability of improved ant colony algorithm is superior to the basic ant colony algorithm, verify the effectiveness of the improvement measures.