Abstract
Assembly path planning (APP) for complex products is challenging due to the large number of parts and intricate coupling requirements. A hybrid assembly path planning method is proposed herein that reuses a priori paths to improve the efficiency and success ratio. The assembly path is initially segmented to improve its reusability. Subsequently, the planned assembly paths are employed as a priori paths to establish an a priori tree, which is expanded according to the bounding sphere of the part to create the a priori space for path searching. Three rapidly exploring random tree (RRT)-based algorithms are studied for path planning based on a priori path reuse. The RRT* algorithm establishes the new path exploration tree in the early planning stage when there is no a priori path to reuse. The static RRT* (S-RRT*) and dynamic RRT* (D-RRT*) algorithms form the connection between the exploration tree and the a priori tree with a pair of connection points after the extension of the exploration tree to a priori space. The difference between the two algorithms is that the S-RRT* algorithm directly reuses an a priori path and obtains a new path through static backtracking from the endpoint to the starting point. However, the D-RRT* algorithm further extends the exploration tree via the dynamic window approach to avoid collision between an a priori path and obstacles. The algorithm subsequently obtains a new path through dynamic and non-continuous backtracking from the endpoint to the starting point. A hybrid process combining the RRT*, S-RRT*, and D-RRT* algorithms is designed to plan the assembly path for complex products in several cases. The performances of these algorithms are compared, and simulations indicate that the S-RRT* and D-RRT* algorithms are significantly superior to the RRT* algorithm in terms of the efficiency and success ratio of APP. Therefore, hybrid path planning combining the three algorithms is helpful to improving the assembly path planning of complex products.
Highlights
A hybrid planning method that reuses a priori paths was proposed in this paper to improve the efficiency and success ratio of path planning
An a priori path set is established according to the planned assembly paths; on this basis, an a priori tree is established
An a priori space is created by expanding the a priori tree according to the bounding sphere of the part to be assembled, which establishes a foundation for path reuse
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Most of the APP methods mentioned above involve a large amount of repeated computation, leading to low planning efficiency and high costs when generating the assembly path through all parts. In these studies, the rapidly exploring random tree (RRT) is a typical random sampling algorithm in path planning which explores free space by generating leaf nodes randomly and uniformly to expand a tree structure. A hybrid path planning method based on the improved RRT* algorithm is proposed in this paper to plan the motion segments as paths with different starting points and the same target point by reusing the planned paths.
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