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Poramate Manoonpong, Frank Pasemann, Hubert Roth


In this article, a modular neurocontroller is presented. It has the capability to generate a reactive behavior of walking machines. The neurocontroller is formed on the basis of a modular structure. It consists of the three different functionality modules: neural preprocessing, a neural oscillator network and velocity regulating networks. Neural preprocessing is for sensory signal processing. The neural oscillator network, based on a central pattern generator, generates the rhythmic movement for basic locomotion of the walking machines while the velocity regulating networks change the walking directions of the machines with respect to the sensory inputs. As a result, this neurocontroller enables the machines to explore in- and out-door environments by avoiding obstacles and escaping from corners or deadlock situations. It was firstly developed and tested on a physical simulation environment, and then was successfully transferred to the six-legged walking machine AMOS-WD06.


Walking machines; recurrent neural networks; locomotion control; autonomous robots; modular neural control; obstacle avoidance; sensor-driven reactive behavior; neural oscillator network; central pattern generators

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