Scholarly Research Excellence

Frank Pasemann

Publications

1

Publications

1
11240
Reactive Neural Control for Phototaxis and Obstacle Avoidance Behavior of Walking Machines
Abstract:
This paper describes reactive neural control used to generate phototaxis and obstacle avoidance behavior of walking machines. It utilizes discrete-time neurodynamics and consists of two main neural modules: neural preprocessing and modular neural control. The neural preprocessing network acts as a sensory fusion unit. It filters sensory noise and shapes sensory data to drive the corresponding reactive behavior. On the other hand, modular neural control based on a central pattern generator is applied for locomotion of walking machines. It coordinates leg movements and can generate omnidirectional walking. As a result, through a sensorimotor loop this reactive neural controller enables the machines to explore a dynamic environment by avoiding obstacles, turn toward a light source, and then stop near to it.
Keywords:
Recurrent neural networks, Walking robots, Modular neural control, Phototaxis, Obstacle avoidance behavior.