A collision avoidance model based on the Lobula giant movement detector (LGMD) neuron of the locust

Abstract

In insects, we can find very complex and compact neural structures that are task specific. These neural structures allow them to perform complex tasks such as visual navigation, including obstacle avoidance, landing, self-stabilization, etc. Obstacle avoidance is fundamental for successful navigation, and it can be combined with more systems to make up more complex behaviors. In this paper, we present a model for collision avoidance based on the Lobula giant movement detector (LGMD) cell of the locust. This is a wide-field visual neuron that responds to looming stimuli and that can trigger avoidance reactions whenever a rapidly approaching object is detected. Here, we present result based on both an offline study of the model and its application to a flying robot.