Presentation | 2005-10-14 A neuromorphic system for recognition of an approaching object inspired by insect vision Hirotsugu OKUNO, Tetsuya YAGI, |
---|---|
PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | We designed a neuromorphic vision sensor to detect a looming object in real time. To respond selectively to looming stimuli, the sensor employs an algorithm inspired by a visual nervous system in a locust, which can avoid a collision robustly by use of visual infomation. We devised a model which consists of passive electric circuit elements and confirmed that the model provides similar infomation to that of locust visual system. After testing the performance of the model, we realized a compact system with a silicon retina and FPGA circuits. The system showed a strong response to looming stimuli. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | collision avoidance / insect vision / bioinspired / silicion retina |
Paper # | MBE2005-83 |
Date of Issue |
Conference Information | |
Committee | MBE |
---|---|
Conference Date | 2005/10/7(1days) |
Place (in Japanese) | (See Japanese page) |
Place (in English) | |
Topics (in Japanese) | (See Japanese page) |
Topics (in English) | |
Chair | |
Vice Chair | |
Secretary | |
Assistant |
Paper Information | |
Registration To | ME and Bio Cybernetics (MBE) |
---|---|
Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | A neuromorphic system for recognition of an approaching object inspired by insect vision |
Sub Title (in English) | |
Keyword(1) | collision avoidance |
Keyword(2) | insect vision |
Keyword(3) | bioinspired |
Keyword(4) | silicion retina |
1st Author's Name | Hirotsugu OKUNO |
1st Author's Affiliation | Graduate School of Engineering, Osaka University() |
2nd Author's Name | Tetsuya YAGI |
2nd Author's Affiliation | Graduate School of Engineering, Osaka University |
Date | 2005-10-14 |
Paper # | MBE2005-83 |
Volume (vol) | vol.105 |
Number (no) | 335 |
Page | pp.pp.- |
#Pages | 4 |
Date of Issue |