期刊
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
卷 42, 期 3, 页码 2681-2693出版社
IOS PRESS
DOI: 10.3233/JIFS-211801
关键词
Path planning; path optimization; hybrid optimization; mobile robot; improved particle swarm optimization
Path planning is a crucial element in mobile robot decision making and control. This research proposes a hybrid optimized path planning model using improved particle swarm optimization and modified whale optimization models, which can achieve the shortest, smoothest, and safest path.
In the field of mobile robot decision making and control, path planning is an essential element as it defines the performance of the design. It is one of the hot topics in artificial intelligence and researchers pay more attention to develop an efficient model. The key requirements that must be considered while designing a navigational system for mobile robots are origin point, obstacles, destination point, path planning, and realistic decision mechanism. However, conventional systems have limitations as slow response, long planning, large turns, and unsafe factors Aiming at the problems, this research work presents a hybrid optimized path planning model for a mobile robot. Improved particle swarm optimization and Modified Whale optimization models are incorporated as a hybrid multi-objective approach to obtain the shortest, smoothest, and safest path for a mobile robot. Experimental results demonstrate that the proposed hybrid optimization model is suitable for mobile robot navigation for dynamic environments by obtaining a shorter, smoother, and safer path than existing algorithms.
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