Target object tracking based on visual serving

Abstract

In the humanoid robot system, we used two computers responsible for visual information processing system and motion control system respectively. The visual platform of the humanoid robot is designed the same as the human head, which can search for the target object in a wide range. The target object tracking process consist of four cycle steps: search, match, refreshing and forecasting; the grasping object process contains five steps: find and coarse positioning target object, walking close to the target object, based on the visual feedforward coarse alignment, fine alignment based on visual feedback, grasp. Each step requires a different control strategy. In experiments, we use the motion capture system to measure the three-dimensional position of the target object, and as a benchmark to measure the measurement accuracy of the humanoid robot vision platform. Experiments show that based on the visual platform, the visual feedforward and the visual feedback control strategy, the target object tracking accuracy has been improved.