Engineering Mechanics

Proceedings Vol. 17 (2011)

ENGINEERING MECHANICS 2011

Copyright © 2011 Institute of Thermomechanics, Academy of Sciences of the Czech Republic, v.v.i., Prague

 

Krejsa J., Věchet S.
pages 327 - 330, full text

Motion planning is essential for mobile robot successful navigation. There are many algorithms for motion planning under various constraints. However, in some cases the human can still do a better job, therefore it would be advantageous to create a planner based on data gathered from the robot simulation when humans do the planning. The paper presents the method of using the neural network to transfer the previously gained knowledge into the machine learning based planner. In particular the neural network task is to mimic the planner based on finite state machine. The tests proved that neural network can successfully learn to navigate in constrained environment.

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