中文摘要：

针对复杂环境中机器人路径规划问题，为了提高蚁群算法的寻优能力和收敛速度，基于A。算法的距离评价函数，对算法中的启发式函数进行改进，提出一种启发式的蚂蚁算法，并对新算法进行仿真测试．结果表明：改进后的启发函数可以有效改善蚂蚁算法搜索的盲目性，解决了传统蚁群算法收敛速度慢、易陷入局部最优解的问题．与传统蚂蚁算法相比，启发式蚂蚁算法在20×20网格下的相关系数提高了0．4722，40×40网格下的相关系数提高了0．2265，说明改进算法的规划能力和收敛效率均有所提高，整体上优于传统蚂蚁算法．

英文摘要：

In order to improve the optimization ability and convergence speed of the a｜gorithm, a heuristic ant algorithm was proposed according to improve the heuristic function in the algorithm based on the distance evaluation function of A＊ algorithm for the problem of the robot path planning in the complex environment, and the simulation experiment was taken to prove the effect. The results show that the new heuristic function can improve the blindness of the traditional ant algorithm, and solve the problems such as the slow convergence rate and algorithm easily falling into the local optimal solution. The correla- tion coefficient of the heuristic ant algorithm in 20 × 20 grid is increased 0.472 2 higher than the traditional algorithm, and the correlation coefficient in 40 × 40 grid is increased 0.226 5 higher than the traditional one. The resuhs illustrate that the planning ability and the convergence rate of the new heuristic ant algorithm is better than that of the traditional ant algorithm, and excel than that of traditional ant algorithm in general.