Parallel Processing, Neural Networks and Genetic Algorithms for Real-Time Robot Control
This chapter reports on recent research on advanced motion planning and control of articulated and mobile robotic systems. In addition to employing the principles of distributed and parallel processing to produce feasible real-time multi-processor networks, other new theories such as neural networks and genetic algorithms are deployed as possible solutions. All reported algorithms are implemented for either the PUMA 560 arm or the B12 mobile robot. The ultimate aim of the on-going research is to present working architectures for real-time robotic systems by augmenting all developed structures.
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