Self-repairing mobile robotic car using astrocyte-neuron networks

A self-repairing robot utilising a spiking astrocyte-neuron network is presented in this paper. It uses the output spike frequency of neurons to control the motor speed and robot activation. A software model of the astrocyte-neuron network previously demonstrated self-detection of faults and its sel...

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Bibliographic Details
Main Authors: Junxiu Liu, Harkin, Jim, McDaid, Liam, Halliday, David M., Tyrrell, Andy M., Timmis, Jon
Format: Conference Proceeding
Language:English
Subjects:
astrocyte
Autonomous automobiles
Computational modeling
DC motors
Fault tolerance
fault-tolerant
Hardware
Neurons
repair
robot car
self-adaptive
spiking neural networks
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Summary:A self-repairing robot utilising a spiking astrocyte-neuron network is presented in this paper. It uses the output spike frequency of neurons to control the motor speed and robot activation. A software model of the astrocyte-neuron network previously demonstrated self-detection of faults and its self-repairing capability. In this paper the application demonstrator of mobile robotics is employed to evaluate the fault-tolerant capabilities of the astrocyte-neuron network when implemented in a hardware-based robotic car system. Results demonstrated that when 20% or less synapses associated with a neuron are faulty, the robot car can maintain system performance and complete the task of forward motion correctly. If 80% synapses are faulty, the system performance shows a marginal degradation, however this degradation is much smaller than that of conventional fault-tolerant techniques under the same levels of faults. This is the first time that astrocyte cells merged within spiking neurons demonstrates a self-repairing capabilities in the hardware system for a real application.
ISSN:2161-4407
DOI:10.1109/IJCNN.2016.7727359