Abstract
The problem of adaptive trajectory planning for robots under stochastic uncertainty is considered, where new information about the robots and their environment is presented on-line. Solving the problem numerically by means of spline approximation and by applying the method of neural networks, the optimal control can be calculated in real-time. Some numerical results are presented.
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Marti, K., Qu, S. Path Planning for Robots by Stochastic Optimization Methods. Journal of Intelligent and Robotic Systems 22, 117–127 (1998). https://doi.org/10.1023/A:1007976516339
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DOI: https://doi.org/10.1023/A:1007976516339