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Training of a leaning agent for Navigation-inspired by brain-Machine interface

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2 Author(s)
T. Kitamura ; Dept. of Mech. Syst. Eng., Kyushu Inst. of Technol., Fukuoka, Japan ; D. Nishino

The design clue for the remote control of a mobile robot is inspired by the Talwar's brain-machine interface technology for remotely training and controlling rats. Our biologically inspired autonomous robot control consciousness-based architecture (CBA) is used for the remote control of a robot as a substitute for a rat. CBA is a developmental hierarchy model of the relationship between consciousness and behavior, including a training algorithm. This training algorithm computes a shortcut path to a goal using a cognitive map created based on behavior obstructions during a single successful trial. However, failures in reaching the goal due to errors of the vision and dead reckoning sensors require human intervention to improve autonomous navigation. A human operator remotely intervenes in autonomous behaviors in two ways: low-level intervention in reflexive actions and high-level ones in the cognitive map. Experiments are conducted to test CBA functions for intervention with a joystick for a Khepera robot navigating from the center of a square obstacle with an open side toward a goal. Their statistical results show that both human interventions, especially high-level ones, are effective in drastically improving the success rate of autonomous detours.

Published in:

IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)  (Volume:36 ,  Issue: 2 )