AN IMPROVED RRT ALGORITHM FOR CRANE PATH PLANNING

Di Wu, Yujie Sun, Xin Wang, and Xiaoli Wang

Keywords

Crane, path planning, rapidly exploring random trees (RRT),Bspline

Abstract

Rapidly exploring random tree (RRT) algorithm is a commonly applied algorithm in path planning. However, it has disadvantages such as some long and smoothless paths. This makes the crane to continuously change its actions with more than 1,000 tons of weight. Furthermore, the force and the centre of gravity of whole lifting system keep changing during the lifting process, which significantly provokes the high-level risk for the security. As a result, RRT cannot directly apply to the crane movement in practice. In this paper, an improved RRT-Tailor-Spline (RRT-TS) algorithm is proposed. Firstly, to shorten the planned path, this algorithm goes through high-quality nodes with sampling pool and uses these nodes to tailor the spanning tree during the growth process. Secondly, the path points are taken as key nodes for the B-spline basic function to imitate a high-dimensional smooth path for crane. With this method, the lifting safety is further improved. In addition, for mobile crane, simulations are carried out corresponding to an actual lifting case to show the effectiveness of our algorithm. Both field simulation and test results show that the RRT-TS algorithm is better than RRT-Connect++ algorithm in the quality of the planned path and it has more applications in mobile crane.

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