Abstract

Manually planning a crane's lifting path is complicated and laborious since it typically depends on the planner's experience. We examined dynamic three-dimensional lift planning, including problem formulation for multiobjective planning and problem-solving with an improved A* algorithm. First, we quantified various feasible movements by introducing energy and time consumption models to determine the most efficient and quickest path. Second, we examined a new method for determining the visible lifting path in Configuration space (C-space) and derived an obstacle enveloping method for collision detection in C-space. Our method is both safe and feasible. Finally, we proposed an improved A* algorithm for lift planning considering multiple objectives and featuring better computational efficiency. The experimental and simulation results demonstrate that the proposed lift planning method can comprehensively consider multiple objectives, thus providing a high-quality path for actual lifting. Furthermore, compared with the ordinary A* algorithm, the improved A* algorithm had better computational efficiency and consumed less energy and time. To our best knowledge, this is the first novel algorithm for planning crane lifts considering energy consumption and visibility in C-space.

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