Tracking of moving targets in complex environments

Abstract

The tracking of a moving target algorithm based on the traditional visual servo can not introduce image and physical constraints, and does not consider the problems such as the features beyond the camera field of view, the robotic arm’s out-of-motion space, and the robotic arm reaching the joint limit. Moreover, the tracking accuracy and stability of the moving target continue to be poor in complex environments (such as the chaotic background, the illumination changes, and the target is partially occluded), and the recognition of the target image is extremely strict, In this paper, a new method of tracking and grasping moving targets is proposed by combining the pose estimation of targets with the tracking and grasping of industrial robots. Kalman filter is used to compensate for the time delay. This method avoids the influence of traditional methods on target depth estimation and image and physical constraints and has strong robustness.