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为了减少移动机器人自主导航过程中过多寻求当前时刻最优路径或最优解而产生的死锁或震荡现象,根据多目标优化理论,提出了基于模糊行为融合的移动机器人避障算法.该算法把指定目标的导航过程分解为具有三个子行为的系统,根据传感器信息动态改变各子行为函数的区间权重和优先级,实时获得当前时刻最满意路径或最有效路径.实验结果证明:该算法可以有效减少导航过程中的死锁和震荡现象,提高避障过程的鲁棒性和实时性.
In order to reduce the deadlock or oscillation caused by seeking too much current optimal path or optimal solution during autonomous navigation of mobile robot, a moving robot obstacle avoidance algorithm based on fuzzy behavior fusion is proposed based on multi-objective optimization theory. The navigation process of a given target is decomposed into three sub-systems, and the weight and priority of each sub-function are dynamically changed according to the sensor information to obtain the most satisfied or the most effective path in real time. Experimental results show that the algorithm can Effectively reduce deadlocks and shocks during navigation, and improve the robustness and real-time performance of the obstacle avoidance process.