Global optimization of mobile robot based on fusion A*-ant colony optimization algorithm
Aiming at the problems of traditional ant colony algorithm in global path planning of indoor mobile robot,such as low search efficiency,unsmooth path,easy to fall into local optimum and deadlock,an ant colony optimization algorithm for bi-direc-tional search with improved A*algorithm was designed.Firstly,the improved A*algorithm was used to quickly converge and ob-tain the initial path in the grid environment,the initial pheromone matrix was constructed,and the obstacle factor was introduced to reduce the occurrence of ant deadlock.Secondly,the rules of ant colony optimization algorithm for bi-directional search were set,the heuristic function model in bi-directional search was improved,and elite ant search strategy and adaptive pheromone volat-ilization factor strategy were introduced.Finally,the third-order Bezier curve was used to smooth the path.The simulation results on Pycharm platform show that this algorithm combines the strong global search ability of A*algorithm and the positive feedback characteristics of ant colony algorithm,which makes the improved algorithm optimize the path length by 12.85％and 7.76％,the search time by 38.17％and 23.46％,and the iteration times by 67.71％and 54.41％compared with the traditional ant colony algorithm and the sparrow search algorithm,and the global path optimization effect is obvious.
mobile robotA*algorithmant colony algorithmbi-directional search pathBezier curve
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