Name
Abstract | ||
|---|---|---|
The lobula giant movement detector (LGMD) system in the locust responds selectively to objects approaching the animal on a collision course. In earlier work we have presented a neural network model based on the LGMD system which shared this preference for approaching objects. We have extended this model in order to evaluate its responses in a real-world environment using a miniature mobile robot. This extended model shows reliable obstacle detection over an eight-fold range of speeds, and raises interesting questions about basic properties of the biological system. (C) 2000 Elsevier Science B.V. All rights reserved. |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1016/S0921-8890(99)00063-9 | ROBOTICS AND AUTONOMOUS SYSTEMS |
Keywords | Field | DocType |
insect vision,lobula giant movement detector (LGMD),mobile robot,obstacle detection,collision avoidance | Computer vision,Obstacle,Lobula giant movement detector,Locust,Computer science,Simulation,Collision,Artificial intelligence,Artificial neural network,Mobile robot,Insect vision | Journal |
Volume | Issue | ISSN |
30 | 1-2 | 0921-8890 |
Citations | PageRank | References |
35 | 4.82 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mark Blanchard | 1 | 85 | 12.52 |
| F Claire Rind | 2 | 198 | 18.13 |
| Paul F. M. J. Verschure | 3 | 188 | 29.61 |