scholarly journals Status of recent developments in collision avoidance using motion detectors based on insect vision

1997 ◽  
Author(s):  
Derek Abbott ◽  
Alireza Moini ◽  
Andre Yakovleff ◽  
X. Thong Nguyen ◽  
R. Beare ◽  
...  
Keyword(s):  
Collision Avoidance ◽  
Insect Vision ◽  
Recent Developments ◽  
Motion Detectors

Characterization of insect vision based collision avoidance models using a video camera

2005 ◽  
Author(s):  
R. Guzinski ◽  
K. Nguyen ◽  
Z. H. Yong ◽  
S. Rajesh ◽  
D. C. O'Carroll ◽  
...  
Keyword(s):  
Collision Avoidance ◽  
Video Camera ◽  
Insect Vision

Civil Marine Radar – A Review and a Way Ahead

1998 ◽  
Vol 51 (3) ◽  
pp. 394-403 ◽  
Author(s):  
P. D. L. Williams
Keyword(s):  
Collision Avoidance ◽  
Future Development ◽  
Cost Effective ◽  
Short History ◽  
Modus Operandi ◽  
Effective Manner ◽  
The Future ◽  
Recent Developments ◽  
Marine Radar

Civil Marine Radar (CMR) is now a mature instrument of some 50 years steady development. Following a short history, more to provide benchmarks of achievement than to satisfy historians, this paper examines what will drive the future development of CMR. The answer may not follow recent developments, but may well be the result of a fresh maritime modus operandi to fulfil the navigation, collision avoidance and safe passage needs of all types of craft operating in all types of water with different pressures and Operational Requirements (ORS). Having postulated fresh ORS, suggestions are made on how best to fulfil them in a logical and cost-effective manner.

From insect vision to robot vision

1992 ◽  
Vol 337 (1281) ◽  
pp. 283-294 ◽  
Keyword(s):  
Feedback Loop ◽  
Compound Eye ◽  
Robot Vision ◽  
Insect Vision ◽  
Visually Guided ◽  
Visuomotor System ◽  
Front End ◽  
Passive Ranging ◽  
Passive Sensors ◽  
Motion Detectors

Airborne insects are miniature w ing-flapping aircraft the visually guided manoeuvres of which depend on analogue, ‘fly-by-wire’ controls. The front-end of their visuomotor system consists of a pair of com pound eyes which are masterpieces of integrated optics and neural design. They rely on an array of passive sensors driving an orderly analogue neural network. We explored in concrete terms how motion-detecting neurons might possibly be used to solve navigational tasks involving obstacle avoidance in a creature whose wings are exquisitely guided by eyes with a poor spatial resolution. We designed, simulated, and built a complete terrestrial creature which moves about and avoids obstacles solely by evaluating the relative motion between itself and the environment. The compound eye uses an array of elementary motion detectors (emds) as smart, passive ranging sensors. Like its physiological counterpart, the visuomotor system is based on analogue, continuous-time processing and does not make use of conventional computers. It uses hardly any memory to adjust the robot’s heading in real time via a local and intermittent visuomotor feedback loop. This paper shows that the understanding of some invertebrate sensory-motor systems has now reached a level able to provide valuable design hints. Our approach brings into prominence the mutual constraints in the designs of a sensory and a motor system, in both living and non-living ambulatory creatures.

New VLSI smart sensor for collision avoidance inspired by insect vision

1995 ◽  
Author(s):  
Derek Abbott ◽  
Alireza Moini ◽  
Andre Yakovleff ◽  
X. Thong Nguyen ◽  
Andrew Blanksby ◽  
...  
Keyword(s):  
Collision Avoidance ◽  
Insect Vision ◽  
Smart Sensor

scholarly journals Neural mechanisms to exploit positional geometry for collision avoidance

2021 ◽  
Author(s):  
Ryosuke Tanaka ◽  
Damon A. Clark
Keyword(s):  
Collision Avoidance ◽  
Visual Motion ◽  
Neural Circuit ◽  
Spatial Information ◽  
Three Dimensional ◽  
Spatial Vision ◽  
Geometrical Constraints ◽  
Three Dimensional Configuration ◽  
Motion Detectors ◽  
Visual Neuron

Visual motion provides rich geometrical cues about the three-dimensional configuration the world. However, how brains decode the spatial information carried by motion signals remains poorly understood. Here, we study a collision avoidance behavior in Drosophila as a simple model of motion-based spatial vision. With simulations and psychophysics, we demonstrate that walking Drosophila exhibit a pattern of slowing to avoid collisions by exploiting the geometry of positional changes of objects on near-collision courses. This behavior requires the visual neuron LPLC1, whose tuning mirrors the behavior and whose activity drives slowing. LPLC1 pools inputs from object- and motion-detectors, and spatially biased inhibition tunes it to the geometry of collisions. Connectomic analyses identified circuitry downstream of LPLC1 that faithfully inherits its response properties. Overall, our results reveal how a small neural circuit solves a specific spatial vision task by combining distinct visual features to exploit universal geometrical constraints of the visual world.

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