Abstract
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.
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Pandey, P., Shukla, A. & Tiwari, R. Three-dimensional path planning for unmanned aerial vehicles using glowworm swarm optimization algorithm. Int J Syst Assur Eng Manag 9, 836–852 (2018). https://doi.org/10.1007/s13198-017-0663-z
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DOI: https://doi.org/10.1007/s13198-017-0663-z