Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
Discrete & Computational Geometry - ACM Symposium on Computational Geometry, Waterloo
An algorithm for planning collision-free paths among polyhedral obstacles
Communications of the ACM
Robot Motion Planning
Genetic Algorithms and Robotics
Genetic Algorithms and Robotics
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Robot Motion: Planning and Control
Robot Motion: Planning and Control
RapidAccurate Optimization of Difficult Problems Using Fast Messy Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
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We are presenting in this work a method to calculate collision free paths, for redundant and non redundant robots, through an adaptation of the Messy Genetic Algorithm with a fitness function weakly defined. The adaptation consists in replacing the two crossing operators (cut and splice) traditionally used by a mechanism similar to that one used in the simple genetic algorithm. Nevertheless, the mechanism presented in this work was designed to work with variable length strings. The main advantages of this method are: even though the fitness function is weakly defined good solutions can be obtained; it does not need a previous discretization of the work space; and it works directly within such space without needing any transformation as in the C-space method. In this work, the fitness function is defined as a linear combination of values which are easily calculated.