Abstract
To improve the path planning efficiency of a robotic arm in three-dimensional space and improve the obstacle avoidance ability, this paper proposes an improved artificial potential field and rapid expansion random tree (APF-RRT) hybrid algorithm for the mechanical arm path planning method. The improved APF algorithm (I-APF) introduces a heuristic method based on the number of adjacent obstacles to escape from local minima, which solves the local minimum problem of the APF method and improves the search speed. The improved RRT algorithm (I-RRT) changes the selection method of the nearest neighbor node by introducing a triangular nearest neighbor node selection method, adopts an adaptive step and generates a virtual new node strategy to explore the path, and removes redundant path nodes generated by the RRT algorithm, which effectively improves the obstacle avoidance ability and efficiency of the algorithm. Bezier curves are used to fit the final generated path. Finally, an experimental analysis based on Python shows that the search time of the hybrid algorithm in a multi-obstacle environment is reduced to 2.8 s from 37.8 s (classic RRT algorithm), 10.1 s (RRT* algorithm), and 7.4 s (P_RRT* algorithm), and the success rate and efficiency of the search are both significantly improved. Furthermore, the hybrid algorithm is simulated in a robot operating system (ROS) using the UR5 mechanical arm, and the results prove the effectiveness and reliability of the hybrid algorithm.
Highlights
In recent years, China’s logistics industry has developed rapidly to meet the increasing demand for e-commerce in response to the internet economy and the rapid development of warehousing automation technology [1]
Zhang et al [9] proposed a path planning method for multiple underwater unmanned vehicles (UUVs) in a three-dimensional environment based on the “domain”, which solves the disadvantages of unreachable targets near obstacles, local minima, and oscillations encountered in the classic artificial potential field (APF) method
If it is detected that the minimum distance between the current node and the obstacle is greater than twice the step length, it means that there is no obstacle near the current node, and the improved APF algorithm (I-APF) method is used for rapid expansion
Summary
China’s logistics industry has developed rapidly to meet the increasing demand for e-commerce in response to the internet economy and the rapid development of warehousing automation technology [1]. The intelligent robotic arm industry is developing rapidly. The robotic arm, as its name implies, is designed to imitate a human arm for moving, grasping, lifting, and loading objects, among other operations [2]. Robotic arms are widely used in the logistics and warehousing industry. To grasp a specified object and place it in the specified position, it is necessary to bypass complex obstacles and find an efficient and collision-free path, which is very simple for humans but presents many technical problems that need to be considered for the robotic arm. For the robotic arm, its path planning is one of the most important technical problems. Successful path planning can greatly improve the storage and grabbing efficiency and has long been a research hotspot in robotic applications.
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