Research Area:  Metaheuristic Computing

Abstract:

The three-dimensional (3D) path planning of unmanned robots focuses on avoiding collisions with obstacles and finding an optimized path to the target location in a complex three-dimensional environment. An improved cuckoo search algorithm based on compact and parallel techniques for three-dimensional path planning problems is proposed. This paper implements the compact cuckoo search algorithm, and then, a new parallel communication strategy is proposed. The compact scheme can effectively save the memory of the unmanned robot. The parallel scheme can increase the accuracy and achieve faster convergence. The proposed algorithm is tested on several selected functions and three-dimensional path planning. Results compared with other methods show that the proposed algorithm can provide more competitive results and achieve more efficient execution.

Keywords:  
three-dimensional
path planning
unmanned robots
collisions
obstacles
communication strategy
accuracy

Author(s) Name:  Pei-Cheng Song, Jeng-Shyang Pan, Shu-Chuan Chu

Publisher name:  Elsevier

DOI:  https://doi.org/10.1016/j.asoc.2020.106443

Volume Information:  Volume 94

Paper Link:   https://www.sciencedirect.com/science/article/abs/pii/S1568494620303835