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针对移动机器人路径规划研究中,移动机器人路径规划易陷入局部极小值,缺乏全局指导性及路径规划效率不高,甚至目的地不可达的问题,这里给出相应的研究方法。通过合理布局超声波探头位置,利用改进人工势场法进行移动机器人的路径规划;对移动机器人陷入局部极小值点的问题,采用入侵杂草算法在全局内有指导性的产生最优子目的地,并根据子目的地重新分配空间内的引力势,引导移动机器人摆脱“陷阱”。Matlab仿真实验表明,本文提出的路径规划算法不仅在一般环境中,而且在相对复杂的环也能引导陷入局部极小值点的移动机准确、安全到达指定目的地。为此算法主要参数选取匹配合理时,可对路径进行优化。该算法在解决局部极小值点的问题具有较高全局指导性。
In the research of mobile robot path planning, the path planning of mobile robot is apt to fall into local minima, lack of global guidance, and inefficient path planning, or even unreachable destination. The corresponding research methods are given here. By arranging the position of the ultrasonic probe properly, the path planning of the mobile robot is improved by using the improved artificial potential field method. For the problem that the mobile robot falls into the local minimum point, the weed intrusion algorithm is used to guide the optimal sub-destination globally , And guide the mobile robot to get rid of “Trap ” according to the gravitational potential in the sub-destination redistribution space. Matlab simulation results show that the path planning algorithm proposed in this paper can guide mobile machines that fall into the local minima to reach the appointed destinations accurately and safely not only in the general environment but also in the relatively complicated rings. For this reason, when choosing the main parameters of the algorithm is reasonable, the path can be optimized. This algorithm has a higher global guideline in solving the problem of local minima.