Collision avoidance in a robot using looming detectors from a locust

F. Claire Rind; Mark Blanchard; Paul F. M. J. Verschure

doi:10.1117/12.403713

16 October 2000 Collision avoidance in a robot using looming detectors from a locust

F. Claire Rind, Mark Blanchard, Paul F. M. J. Verschure

Proceedings Volume 4196, Sensor Fusion and Decentralized Control in Robotic Systems III; (2000) https://doi.org/10.1117/12.403713
Event: Intelligent Systems and Smart Manufacturing, 2000, Boston, MA, United States

Abstract

The superb aerial performance of flying insects is achieved with comparatively simple neural machinery. We have been investigating the pathway in the locust visual system that signals the rapid approach of an object towards the eye. Two identified neurons have been shown to respond selectively to the images of an object approaching the locust's eye. A neural network based on the input organization of these neurons responds directionally when challenged with approaching and receding objects and reveals the importance of a critical race, between excitation passing down the network and inhibition directed laterally, for the rapid build-up of excitation in response to approaching objects. The strongest response is given to an object approaching on a collision course with they eye, when collision is imminent. Like the neurons, the network is tightly tuned to a collision trajectory. We have incorporated this network into the control structure of a small mobile Kephera robot using the IQR 4021 software we developed. The network responds to looming motion and is effective at evoking avoidance maneuvers in the robot, moving at speeds from 1-12.5cm/s. Our aim is to use the circuit as an artificial looming detector for use in moving vehicles.

Citation Download Citation

F. Claire Rind, Mark Blanchard, and Paul F. M. J. Verschure "Collision avoidance in a robot using looming detectors from a locust", Proc. SPIE 4196, Sensor Fusion and Decentralized Control in Robotic Systems III, (16 October 2000); https://doi.org/10.1117/12.403713

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available