Collision-Free Path Planning For Mobile Cranes Based On Ant Colony Algorithm

This paper presents the work done towards searching a collision-free path for mobile crane based on C-space in the complex 3D working environment. The crane is simplified into three degrees of freedom (DOFs) robot, each of which is represented as an axis of configuration space (C-space). In this paper, we propose an improved ant colony approach for crane path planning, which takes into full account of not only the factor of the shortest path but also the factor of safety. In this approach, we employ more complete heuristic information, introduce adaptive pheromone volatilization coefficient and pheromone penalty factors, and prevent ants from falling into trap and the stagnation. The reasonability and practicability of the proposed approach for automated path planning is verified by comparing the performances of the present approaches in the practice case, and the comparison results show that the algorithm can gain a relatively optimal solution in short time and have a great value of engineering application.