Proceedings ArticleDOI
Selfish and coordinative planning for multiple mobile robots by genetic algorithm
Takanori Shibata,Toshio Fukuda,Kazuhiro Kosuge,Fumihito Arai +3 more
- Vol. 3, pp 2686-2691
TLDR
A novel strategy for coordination of multiple autonomous robots by using genetic algorithms (GAs) is presented, which is applied to both the selfish planning and the coordinative planning of multiple mobile robots.Abstract:
A novel strategy for coordination of multiple autonomous robots by using genetic algorithms (GAs) is presented. When a mobile robot moves from a point to a goal point, it is necessary to plan an optimal or feasible path for it, avoiding obstructions in its way and minimizing costs such as time, energy, and distance. This planning is referred to as selfish planning. When many robots move in the same space, it is necessary to select the most reasonable path so as to avoid collisions with other robots and to minimize the cost. This planning is referred to as coordinative planning. The GAs are search algorithms based on the mechanics of natural selection and natural genetics. The GAs are applied to both the selfish planning and the coordinative planning of multiple mobile robots. >read more
Citations
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Proceedings ArticleDOI
A knowledge based genetic algorithm for path planning of a mobile robot
Yanrong Hu,Simon X. Yang +1 more
TL;DR: In this article, a knowledge-based GA for path planning of a mobile robot is proposed, which uses problem-specific genetic algorithms for robot path planning instead of the standard GAs.
Journal ArticleDOI
An intelligent robotic system based on a fuzzy approach
T. Fukuda,Naoyuki Kubota +1 more
TL;DR: This paper focuses on a mobile robotic system with a fuzzy controller and proposes a sensory network that allows the robot to perceive its environment and discusses the effectiveness of the proposed method through computer simulations of collision avoidance and path-planning problems.
An intelligent robotic system based on a fuzzy approach : Special issue on computational intelligence
T. Fukuda,N. Kubota +1 more
TL;DR: In this article, a fuzzy-based intelligent robotic system that requires various capabilities normally associated with intelligence is presented. But the authors focus on a mobile robotic system with a fuzzy controller and propose a sensory network that allows the robot to perceive its environment.
Proceedings ArticleDOI
Genetic algorithm based path planning for a mobile robot
Jianping Tu,Simon X. Yang +1 more
TL;DR: The proposed algorithm is capable of generating collision-free paths for a mobile robot in both static and dynamic environments, and the generated robot path is optimal in the sense of the shortest distance.
Book
Computational Intelligence: Soft Computing and Fuzzy-Neuro Integration with Applications
TL;DR: This book considers the principal constituents of soft computing, namely fuzzy logic, neurocomputing, genetic computing, and probabilistic reasoning, the relations between them, and their fusion in industrial applications, and how the combination can be used to achieve a high Machine Intelligence Quotient.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Genetic algorithms in search, optimization and machine learning
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Book
Handbook of Genetic Algorithms
TL;DR: This book sets out to explain what genetic algorithms are and how they can be used to solve real-world problems, and introduces the fundamental genetic algorithm (GA), and shows how the basic technique may be applied to a very simple numerical optimisation problem.
Journal ArticleDOI
An algorithm for planning collision-free paths among polyhedral obstacles
TL;DR: A collision avoidance algorithm for planning a safe path for a polyhedral object moving among known polyhedral objects that transforms the obstacles so that they represent the locus of forbidden positions for an arbitrary reference point on the moving object.