Robot path planning based on improved ant colony algorithm

It is easy to arise problems such as early search time is long, get stuck at local optimum easily and convergence speed is slow when traditional ant colony algorithm is uesed to path planning, Therefore, this paper put forwards an improved ant colony algorithm. According to the evaluation function of A* algorithm, the heuristic function is optimized, and the weight coefficient is adjusted dynamically and thus raise the efficiency of search path through algorithm, which is conducive to global optimization. The grid method is applied to create obstacle environment for simulation. The experimental results indicate that the improved algorithm can plan a shorter path and the convergence speed is significantly faster.