Neural Control and Learning for Versatile, Adaptive, Autonomous Behavior of Walking Machines

This article presents two different types of walking machines: an insect-like robot and a biped robot which have been developed during last years. Both walking machines are attractive in the way that they now combine three key aspects: versatility, adaptivity, and autonomy. Versatility in this sense means a variety of reactive behaviors, while adaptivity implies to online learning capabilities, and autonomy is an ability to function without continuous human guidance. These three key elements are achieved under neural control and an online learning mechanism. In addition, this contribution will point out that such control technique is shown to be a power method of solving sensor-motor coordination problems of high complexity systems.