Advanced Humanoid Robot Based on the Evolutionary Inductive Self-Organizing Network

Abstract

The bipedal structure is one of the most versatile ones for the employment of walking robots. The biped robot has almost the same mechanisms as a human and is suitable for moving in an environment which contains stairs, obstacle etc, where a human lives. However, the dynamics involved are highly nonlinear, complex and unstable. So it is difficult to generate human-like walking motion. To realize human-shaped and human-like walking robots, we call this as humanoid robot, many researches on the biped walking robots have been reported [1-4]. In contrast to industrial robot manipulators, the interaction between the walking robots and the ground is complex. The concept of the zero moment point (ZMP) [2] is known to give good results in order to control this interaction. As an important criterion for the stability of the walk, the trajectory of the ZMP beneath the robot foot during the walk is investigated [1-7]. Through the ZMP, we can synthesize the walking patterns of humanoid robot and demonstrate walking motion with real robots. Thus ZMP is indispensable to ensure dynamic stability for a biped robot. The ZMP represents the point at which the ground reaction force is applied. The location of the ZMP can be obtained computationally using a model of the robot. But it is possible that there is a large error between the actual ZMP and the calculated one, due to the deviations of the physical parameters between the mathematical model and the real machine. Thus, actual ZMP should be measured to realize stable walking with a control method that makes use of it. In this chapter, actual ZMP data throughout the whole walking phase are obtained from the practical humanoid robot. And evolutionary inductive self-organizing network [8-9] is applied. So we obtained natural walking motions on the flat floor, some slopes, and uneven floor.