2008 Special Issue: A visually guided collision warning system with a neuromorphic architecture

Authors:
Hirotsugu Okuno;Tetsuya Yagi
Affiliations:
Division of Electrical, Electronic and Information Engineering, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan;Division of Electrical, Electronic and Information Engineering, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan
Venue:
Neural Networks
Year:
2008

Citing 2
Cited 1

A bio-inspired visual collision detection mechanism for cars: Optimisation of a model of a locust neuron to a novel environment

Neurocomputing
An analog VLSI chip emulating sustained and transient response channels of the vertebrate retina

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A modified model for the Lobula Giant Movement Detector and its FPGA implementation

Computer Vision and Image Understanding

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Abstract

We have designed a visually guided collision warning system with a neuromorphic architecture, employing an algorithm inspired by the visual nervous system of locusts. The system was implemented with mixed analog-digital integrated circuits consisting of an analog resistive network and field-programmable gate array (FPGA) circuits. The resistive network processes the interaction between the laterally spreading excitatory and inhibitory signals instantaneously, which is essential for real-time computation of collision avoidance with a low power consumption and a compact hardware. The system responded selectively to approaching objects of simulated movie images at close range. The system was, however, confronted with serious noise problems due to the vibratory ego-motion, when it was installed in a mobile miniature car. To overcome this problem, we developed the algorithm, which is also installable in FPGA circuits, in order for the system to respond robustly during the ego-motion.