Strategy creation, decomposition and distribution in particle navigation
Information Sciences: an International Journal
A new methodology of mobile robot navigation: The agoraphilic algorithm
Robotics and Computer-Integrated Manufacturing
Sonar based simultaneous localization and mapping using a neuro evolutionary optimization
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Determination of robot drop location for military path planning using GIS application
CEA'10 Proceedings of the 4th WSEAS international conference on Computer engineering and applications
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
Fuzzy control of autonomous underwater robot using MVFF
ACMOS'06 Proceedings of the 8th WSEAS international conference on Automatic control, modeling & simulation
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A local navigation algorithm for mobile robots is proposed that combines rule-based and neural network approaches. First, the extended virtual force field (EVFF), an extension of the conventional virtual force field (VFF), implements a rule base under the potential field concept. Second, the neural network performs fusion of the three primitive behaviors generated by EVFF. Finally, evolutionary programming is used to optimize the weights of the neural network with an arbitrary form of objective function. Furthermore, a multinetwork version of the fusion neural network has been proposed that lends itself to not only an efficient architecture but also a greatly enhanced generalization capability. Herein, the global path environment has been classified into a number of basic local path environments to which each module has been optimized with higher resolution and better generalization. These techniques have been verified through computer simulation under a collection of complex and varying environments