Real-time robot vision for collision avoidance inspired by neuronal circuits of insects

• Published in: 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems pp. 1302 - 1307
• Main Authors: Okuno, H., Yagi, T.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-10-2007
• Subjects: Circuits; Collision avoidance; Field programmable gate arrays; Hardware; Insects; Nervous system; Robot sensing systems; Robot vision systems; Robustness; Sensor systems
• ISBN: 9781424409112; 142440911X
• ISSN: 2153-0858; 2153-0866
• DOI: 10.1109/IROS.2007.4399089

A real-time vision sensor for collision avoidance was designed. To respond selectively to approaching objects on direct collision course, the sensor employs an algorithm inspired by the visual nervous system in a locust, which can avoid a collision robustly by using visual information. We implemented the architecture of the locust nervous system with a compact hardware system which contains mixed analog- digital integrated circuits consisting of an analog resistive network and field-programmable gate array (FPGA) circuits. 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 car. The system was confirmed to respond selectively to colliding objects even in complicated real-world situations.