Journal ArticleDOI
Robot path planning in uncertain environment using multi-objective particle swarm optimization
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TLDR
Several new operations/improvements such as the particle update method based on random sampling and uniform mutation, the infeasible archive, the constrained domination relationship based on collision times with obstacles, are incorporated into the proposed algorithm to improve its effectiveness.About:
This article is published in Neurocomputing.The article was published on 2013-03-01. It has received 328 citations till now. The article focuses on the topics: Multi-swarm optimization & Metaheuristic.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 ArticleDOI
A survey of human-centered intelligent robots: issues and challenges
TL;DR: This paper provides a comprehensive survey of the recent development of the human-centered intelligent robot and presents a survey of existing works on human- centered robots.
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
An improved genetic algorithm with co-evolutionary strategy for global path planning of multiple mobile robots
Hong Qu,Ke Xing,Takacs Alexander +2 more
TL;DR: This improved GA presents an effective and accurate fitness function, improves genetic operators of conventional genetic algorithms and proposes a new genetic modification operator.
Journal ArticleDOI
Mobile Robot Navigation and Obstacle Avoidance Techniques: A Review
TL;DR: The present article focuses on the study of the intelligent navigation techniques, which are capable of navigating a mobile robot autonomously in static as well as dynamic environments.
References
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Journal ArticleDOI
A fast and elitist multiobjective genetic algorithm: NSGA-II
TL;DR: This paper suggests a non-dominated sorting-based MOEA, called NSGA-II (Non-dominated Sorting Genetic Algorithm II), which alleviates all of the above three difficulties, and modify the definition of dominance in order to solve constrained multi-objective problems efficiently.
Proceedings ArticleDOI
Particle swarm optimization
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
Journal ArticleDOI
Handling multiple objectives with particle swarm optimization
TL;DR: An approach in which Pareto dominance is incorporated into particle swarm optimization (PSO) in order to allow this heuristic to handle problems with several objective functions and indicates that the approach is highly competitive and that can be considered a viable alternative to solve multiobjective optimization problems.
Book ChapterDOI
Multiobjective Optimization Using Evolutionary Algorithms - A Comparative Case Study
Eckart Zitzler,Lothar Thiele +1 more
TL;DR: In this paper an extensive, quantitative comparison is presented, applying four multiobjective evolutionary algorithms to an extended 0/1 knapsack problem.
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