Application of 3-D Path Planning and Obstacle Avoidance Algorithms on Obstacle-Overcoming Robots

Y. Huang, Huang Shi, Wang Hao, Ruifeng Meng
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Abstract

This article presents a MMP algorithm that combines a 3-D path planning algorithm with a DWA obstacle avoidance algorithm, to enable obstacle-overcoming robots to navigate complex, unstructured scenes. To achieve this, a novel A-star algorithm is proposed that can switch to a greedy best-first strategy algorithm based on the characteristics of the scene. The path planning algorithm is integrated with the DWA algorithm, allowing for local dynamic obstacle avoidance while following the global planned path. Additionally, the algorithm enables the robot to correct its path after obstacle avoidance and overcoming. The feasibility and robustness of the algorithms are demonstrated through simulation experiments in a factory with several complex environments. The algorithms quickly generate a reasonable 3-D path and perform reliable local obstacle avoidance, while taking into account the characteristics of the scene and motion obstacles.
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三维路径规划与避障算法在超障机器人中的应用
本文提出了一种MMP算法,该算法结合了三维路径规划算法和DWA避障算法,使克服障碍的机器人能够在复杂的非结构化场景中导航。为了实现这一目标,提出了一种新的a -star算法,该算法可以根据场景的特征转换为贪婪的最佳优先策略算法。将路径规划算法与DWA算法相结合,在遵循全局规划路径的同时实现局部动态避障。此外,该算法使机器人能够在避障和克服障碍后纠正其路径。通过多个复杂环境下的工厂仿真实验,验证了算法的可行性和鲁棒性。该算法在考虑场景和运动障碍物的特点下,快速生成合理的三维路径,并进行可靠的局部避障。
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