A robot that walks; emergent behaviors from a carefully evolved network

Abstract

The author describes a carefully designed series of networks, each one being a strict augmentation of the previous one, which control a six-legged walking machine capable of walking over rough terrain and following a person passively sensed in the infrared spectrum. As the completely decentralized networks are augmented, the robot's performance and behavior repertoire demonstrably improve. The rationale for such demonstrations is that they can help identify requirements for automatically building massive networks to carry out complex sensory-motor tasks. The experiments with an actual robot ensure that an essence reality is maintained and that no critical disabling problems have been ignored. The present work is based on the drawing of analogies between evolution in the animal world and robotic evaluation.