Implementation of the status control system by using environment recognition and motion control

This paper presents the efficient status control system for a biped walking robot. A biped walking robot should have the ability to autonomously recognize its surrounding environment and make right decisions in corresponding to its situation. To solve the problem, we suggest the status control system which has two sub-parts, environment recognition system and motion control system. The environment recognition system transmits the information regarding obstacle conditions to a biped walking robot. We describe an adaboost algorithm as the obstacle region extracting module from input images. Besides, PCA is applied as a feature extracting module from the obstacle region and a hierarchical support vector machine is applied as an obstacle recognizing module. The data from vision system is combined with information from other sensors and the walking assist commands transmit to the biped walking robot. In the motion control system, a robot dynamically generates its walking trajectories of each joint by using neural networks when facing new obstacle such as stairs, and it maintains its walking stability by using closed loop fuzzy method. From the results of experiments, the proposed method can be applied to biped walking robot effectively.