一种基于回溯搜索的生物激励机器人完全遍历路径规划方法

• Format: Patent
• Language: Chinese
• Published: 05.11.2019
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; CONTROLLING; COUNTING; PHYSICS; REGULATING; SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES

本发明公开了一种基于回溯搜索的生物激励机器人完全遍历路径规划方法，该方法融合了生物激励神经网络算法、回溯算法、D*(D Star)算法的优点，实现机器人在复杂环境下的完全遍历路径规划。具体方法为：1)利用生物激励神经网络模型来模拟动态环境，引导机器人进行往复运动；2)当机器人陷入死锁，首先用回溯算法快速找到逃离死锁的目标位置，然后用D*算法规划出一条从当前位置到目标位置的最短路径。本发明不仅保持了生物激励算法生成的路径平滑，转弯较少的优点，还加快了机器人逃离死锁的速度，使机器人能够快速覆盖整个工作空间。本发明不存在局部极小值问题，计算量小，实现简单，在动态未知环境下有很好的适应性。 The invention discloses a biological excitation robot complete traverse path planning method based on backtracking search. The method is combined with the advantages of a biological excitation neural network algorithm, a backtracking algorithm and a D * (D star) algorithm to enable a robot to achieve complete transverse path planning in a complicated environment. The method specifically comprises the steps that 1, the biological excitation neural network model is used for simulating a dynamic environment to guide the reciprocating motion of the robot; 2, when the robot deadlocks, firstly, the backtracking algorithm is used for rapidly finding a target position for escaping from deadlocking, and then, and the D* algorith