Path Planning For Mobile Crane’s Heavy Lifting Based On RRT-Connect++

Recently, the path planning problem for crane lifting has attracted researchers’attentions because crane lifting has been widely applied in the modern lifting engineering. In the theoretical study of crane path planning, the RRT random sampling algorithm is the most commonly algorithm. However, the randomness of RRT algorithm always results in low-quality path for crane and the planned path is too long to follow. What’s more, too many fold lines exist. This means the smoothness of the planned path is not ideal. Such disadvantages will decrease the efficiency and security of the crane lifting task seriously, especially for the large-scale lifting engineering with thousands of tonnage. So this paper analyzes the lifting methods and lifting properties for mobile crane lifting. What’s more, we get a feasible path in real lifting task with the modified RRT-Connect++algorithm, which is short and smooth enough for lifting task.Firstly, in order to overcome difficulties, such that the lifting process cannot be played again and lifting accidents always happen, we give our analysis of path planning software’ drawbacks in present. In addition, we review the research status of crane lifting path planning, modeling and other aspects and state the significance of our study. The organization and structure of this paper are also stated.Secondly, based on study of crane path planning, we analyze the operating principle of mobile crane lifting and build the mathematical model. We give detailed descriptions for the performance constraints, the integrity constraints and closed-loop constraints in the model.Thirdly, we present a simple introduction of the RRT-Connect++algorithm in algorithm flows and implementation details. Then we focus on the modification of RRT-Connect++in the extension of spanning trees and random sampling strategy and study the drawbacks of RRT-Connect++algorithm in path length and smoothness. Simulations are presented to show the correctness of our analysis.Finally, we propose modified RRT-Connect++algorithm by combining key configuration RRT algorithm, artificial potential field method and spline function algorithm. Detailed descriptions of above algorithms are presented. With the modified RRT-Connect++algorithm, we design the lifting path in real lifting task, this shows the correctness and efficiency of our method.