A robot vision system for collision avoidance using a bio-inspired algorithm

Locusts have a remarkable ability of visual guidance that includes collision avoidance exploiting the limited nervous networks in their small cephalon. We have designed and tested a real-time intelligent visual system for collision avoidance inspired by the visual nervous system of a locust. The system was implemented with mixed analog-digital integrated circuits consisting of an analog resistive network and field-programmable gate array (FPGA) circuits so as to take advantage of the real-time analog computation and programmable digital processing. The response properties of the system were examined by using simulated movie images, and the system was tested also in real-world situations by loading it on a motorized miniature car. The system was confirmed to respond selectively to colliding objects even in complex real-world situations.