Three-dimensional path planning for unmanned aerial vehicles using glowworm swarm optimization algorithm

被引：48

作者：

Pandey P. ^{[1
]}

Shukla A. ^{[1
]}

Tiwari R. ^{[1
]}

机构：

[1] Robotics and Intelligent System Design Lab, Indian Institute of Information Technology and Management, Gwalior

来源：

International Journal of System Assurance Engineering and Management | 2018年 / 9卷 / 04期

关键词：

Glowworm swarm optimization; Meta-heuristics; Path planning; Robotics; Swarm intelligence;

D O I：

10.1007/s13198-017-0663-z

中图分类号：

学科分类号：

摘要：

Robot path planning is a task to determine the most viable path between a source and destination while preventing collisions in the underlying environment. This task has always been characterized as a high dimensional optimization problem and is considered NP-Hard. There have been several algorithms proposed which give solutions to path planning problem in deterministic and non-deterministic ways. The problem, however, is open to new algorithms that have potential to obtain better quality solutions with less time complexity. The paper presents a new approach to solving the 3-dimensional path planning problem for a flying vehicle whose task is to generate a viable trajectory for a source point to the destination point keeping a safe distance from the obstacles present in the way. A new algorithm based on discrete glowworm swarm optimization algorithm is applied to the problem. The modified algorithm is then compared with Dijkstra and meta-heuristic algorithms like PSO, IBA and BBO algorithm and their performance is compared to the path optimization problem. © 2017, The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden.

引用

页码：836 / 852

页数：16

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