Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
Simulation of chaotic EEG patterns with a dynamic model of the olfactory system
Biological Cybernetics
Neural computation and self-organizing maps: an introduction
Neural computation and self-organizing maps: an introduction
An Behavior-based Robotics
Cellular Neural Networks
Chaotic neurodynamics for autonomous agents
IEEE Transactions on Neural Networks
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In this paper a new reactive layer for multi-sensory integration applied to robot navigation is proposed. The new robot navigation technique exploits the use of a chaotic system able to be controlled in real-time towards less complex orbits, like periodic orbits or equilibrium points, considered as perceptive orbits. These are subject to real-time modifications on the basis of environment changes acquired through a distributed sensory system. The strategy is inspired to the olfactory bulb neural activity observed in rabbits subject to external stimuli. The mathematical details of the approach are given including simulation results in a virtual environment. Furthermore the proposed strategy has been tested on an experimental environment consisting of an FPGA-based hardware driving an autonomous roving robot. The obtained results demonstrate the capability to perform a real-time navigation control.