doi: 10.7763/IJCTE.2013.V5.803
Lift Path Planning for Telescopic Crane Based-on Improved hRRT
Yuanshan Lin1
,
Xin Wang2 , , ,
Shunde Gao2
- 1School of Computer Science, Dalian University of Technology, Dalian, Liaoning, P.R. China.
- 2School of Mechanical Engineering, Dalian University of Technology, Dalian, Liaoning, P.R. China.
Abstract
The hRRT algorithms based on heuristics can solve many path planning problems, but its efficiency can still be improved. We deeply analyze the details of hRRT, and enhance it by using bi-directional tree and adopting kd-tree as secondary data structure to select nearest neighbors. At last, the improved hRRT is used for lift path planning for telescopic crane, and the efficiency of the improved hRRT is verified. The result of the experiment shows that the enhanced hRRT can dramatically shorten the plan time without reducing the quality of path.
Keywords
- Rapidly-exploring random tree
- hRRT
- path planning
- crane lifting
How to Cite
Yuanshan Lin, Xin Wang, Di Wu, Xiukun Wang, and Shunde Gao, "Lift Path Planning for Telescopic Crane Based-on Improved hRRT," International Journal of Computer Theory and Engineering, vol. 5, no. 5, pp. 816-819, 2013. https://doi.org/10.7763/IJCTE.2013.V5.803
Copyright & License
Copyright © 2013 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).