论文标题
3D路径计划和避免障碍物的算法
3D Path Planning and Obstacle Avoidance Algorithms for Obstacle-Overcoming Robots
论文作者
论文摘要
本文介绍了一种多模式运动计划（MMP）算法，该算法结合了三维（3-D）路径计划和DWA障碍避免算法。该算法旨在计划复杂的非结构化场景中超越障碍物的机器人的路径和运动。提出了一种新颖的A-Star算法来结合非结构化场景的特征，并将其切换为贪婪的最佳优先策略算法的策略。同时，路径计划的算法与DWA算法集成在一起，因此机器人可以在沿着全球计划的路径运动过程中执行局部动态障碍。此外，当提出的全球路径计划算法与局部障碍算法结合使用时，机器人可以在避免障碍物后纠正路径并克服障碍物。具有几个复杂环境的工厂中的仿真实验验证了算法的可行性和鲁棒性。在考虑场景和运动障碍物的特征的前提下，算法可以迅速为超越障碍物的机器人生成合理的3D路径，并在考虑场景和运动障碍的特征的前提下进行可靠的局部障碍。
This article introduces a multimodal motion planning (MMP) algorithm that combines three-dimensional (3-D) path planning and a DWA obstacle avoidance algorithm. The algorithms aim to plan the path and motion of obstacle-overcoming robots in complex unstructured scenes. A novel A-star algorithm is proposed to combine the characteristics of unstructured scenes and a strategy to switch it into a greedy best-first strategy algorithm. Meanwhile, the algorithm of path planning is integrated with the DWA algorithm so that the robot can perform local dynamic obstacle avoidance during the movement along the global planned path. Furthermore, when the proposed global path planning algorithm combines with the local obstacle avoidance algorithm, the robot can correct the path after obstacle avoidance and obstacle overcoming. The simulation experiments in a factory with several complex environments verified the feasibility and robustness of the algorithms. The algorithms can quickly generate a reasonable 3-D path for obstacle-overcoming robots and perform reliable local obstacle avoidance under the premise of considering the characteristics of the scene and motion obstacles.
