Proceedings ArticleDOI
Smooth Path Planning of a Mobile Robot Using Stochastic Particle Swarm Optimization
Xin Chen,Yangmin Li +1 more
- pp 1722-1727
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TLDR
The stochastic PSO (S-PSO) with high exploration ability is developed, so that a swarm with small size can accomplish path planning and to reduce computational cost of optimization.Abstract:
This paper proposes a new approach using improved particle swarm optimization (PSO) to optimize the path of a mobile robot through an environment containing static obstacles. Relative to many optimization methods that produce nonsmooth paths, the PSO method developed in this paper can generate smooth paths, which are more preferable for designing continuous control technologies to realize path following using mobile robots. To reduce computational cost of optimization, the stochastic PSO (S-PSO) with high exploration ability is developed, so that a swarm with small size can accomplish path planning. Simulation results validate the proposed algorithm in a mobile robot path planning.read more
Citations
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Journal ArticleDOI
Heuristic approaches in robot path planning
TL;DR: This survey concentrates on heuristic-based algorithms in robot path planning which are comprised of neural network, fuzzy logic, nature inspired algorithms and hybrid algorithms.
Journal Article
Classic and Heuristic Approaches in Robot Motion Planning A Chronological Review
TL;DR: This paper reviews the major contributions to the Motion Planning field throughout a 35-year period, from classic approaches to heuristic algorithms, and concludes with comparative tables and graphs demonstrating the frequency of each MP method’s application.
Journal ArticleDOI
A hybridization of an improved particle swarm optimization and gravitational search algorithm for multi-robot path planning
TL;DR: The Simulation and the Khepera environment result show outperforms of IPSO–IGSA as compared with IPSO and IGSA with respect to optimize the path length from predefine initial position to designation position, energy optimization in the terms of number of turn and arrival time.
Journal ArticleDOI
Research of biogeography particle swarm optimization for robot path planning
Hongwei Mo,Lifang Xu +1 more
TL;DR: A new method of global path planning by combining BBO, PSO and approximate voronoi boundary network (AVBN) in a static environment is presented and results in simulation show that the proposed method is feasible and effective.
Journal ArticleDOI
Path planning for mobile robot using self-adaptive learning particle swarm optimization
Guangsheng Li,Wusheng Chou +1 more
TL;DR: A novel self-adaptive learning mechanism is developed to adaptively select the most suitable search strategies at different stages of the optimization process, which can improve the search ability of particle swarm optimization (PSO).
References
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Proceedings ArticleDOI
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