Implementing reinforcement learning in the chaotic KIV model using mobile robot AIBO

Abstract

We use the biologically inspired dynamic neural network architecture KIV to achieve robust goal-oriented navigation in a physical environment with obstacles. KIV operates on the principle of chaotic neurodynamics, in the style of brains. It performs the task of multi-sensory fusion, recognition, and decision-making in real time. We use the Sony AIBO robot to demonstrate the operation of our algorithm. AIBO's video camera and infra sensors have been complemented with an external camera for monitoring of the robot's position. The performance of the autonomous system is evaluated using goal-oriented navigation.