Optimization of Robot Arm Motion in Human Environment
نویسندگان
چکیده
In this paper we propose an optimal arm motion generation satisfying multiple criteria via evolved neural controllers. Three different criteria are chosen to be optimized simultaneously, similar to human arm motion in performing daily activities. These criteria are minimum execution time, minimum distance and minimum acceleration. Selected neural controllers from the Pareto solutions are implemented and their performance is evaluated in simulation and on the real mobile robot. Results show a good performance with some differences between simulation and real robot experiments.
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