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.

[1]  Shih-Chung Kang,et al.  Three-Dimensional Simulation and Visualization of Crane Assisted Construction Erection Processes , 2009 .

[2]  Jingan Yang,et al.  An improved ant colony optimization algorithm for solving a complex combinatorial optimization problem , 2010, Appl. Soft Comput..

[3]  Manuela M. Veloso,et al.  Real-time randomized path planning for robot navigation , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[4]  Koshy Varghese,et al.  Automated Path Planning of Cooperative Crane Lifts Using Heuristic Search , 2003 .

[5]  Kazuhiko Terashima,et al.  Path Planning and Obstacle Avoidance Considering Rotary Motion of Load for Overhead Cranes , 2008 .

[6]  Xin Wang,et al.  Design and Realization of Crawler Crane’s Lifting Simulation System , 2008 .

[7]  Mahmoud Tarokh,et al.  Hybrid intelligent path planning for articulated rovers in rough terrain , 2008, Fuzzy Sets Syst..

[8]  Jiang Chang-sheng,et al.  Short communication: A modified ant optimization algorithm for path planning of UCAV , 2008 .

[9]  Marco Dorigo,et al.  Distributed Optimization by Ant Colonies , 1992 .

[10]  Loulin Huang,et al.  Velocity planning for a mobile robot to track a moving target - a potential field approach , 2009, Robotics Auton. Syst..

[11]  Koshy Varghese,et al.  COLLISION FREE PATH PLANNING OF COOPERATIVE CRANE MANIPULATORS USING GENETIC ALGORITHM , 2005 .

[12]  Xin Wang,et al.  Modeling Method of Crawler Crane Based on Open Source Engines , 2010 .

[13]  Steven M. LaValle,et al.  Planning algorithms , 2006 .

[14]  Oscar Castillo,et al.  Path planning for autonomous mobile robot navigation with ant colony optimization and fuzzy cost function evaluation , 2009, Appl. Soft Comput..

[15]  XI Yu-geng.  Hopfield neural networks for path planning in dynamic and unknown environments , 2004 .

[16]  A. R. Soltani,et al.  A fuzzy based multi-objective path planning of construction sites , 2004 .

[17]  Antti Autere.  Hierarchical A* based path planning - a case study , 2002, Knowl. Based Syst..

[18]  Eduardo Miranda,et al.  Planning and visualization for automated robotic crane erection processes in construction , 2006 .

[19]  Burcu Akinci,et al.  Automated generation of workspace requirements of mobile crane operations to support conflict detection , 2007 .

[20]  Mou Chen,et al.  A modified ant optimization algorithm for path planning of UCAV , 2008, Appl. Soft Comput..

[21]  Luca Maria Gambardella,et al.  Ant colony system: a cooperative learning approach to the traveling salesman problem , 1997, IEEE Trans. Evol. Comput..

[22]  Koshy Varghese,et al.  Automated Path Planning for Mobile Crane Lifts , 2002 .

[23]  Hartmut Surmann,et al.  Path planning far a fuzzy controlled autonomous mobile robot , 1996, Proceedings of IEEE 5th International Fuzzy Systems.