Collision avoidance using a model of the locust LGMD neuron

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.

• Type: Journal
• Year: 2000
• Where: RAS
• Authors: Mark Blanchard, F. Claire Rind, Paul F. M. J. Verschure
• Keywords: Miniature Mobile Robot, Neural Network Model, RAS 2000, Reliable Obstacle Detection