Automatic Manipulator Tracking Control Based on Moving Target Trajectory Prediction

Abstract

The core issue of automatic manipulator tracking control is how to ensure the given moving target follows the expected trajectory and adapts to various uncertain factors. However, the existing moving target trajectory prediction methods rely on highly complex and accurate models, lacking the ability to generalize different automatic manipulator tracking scenarios. Therefore, this study tries to find a way to realize automatic manipulator tracking control based on moving target trajectory prediction. In particular, a moving target trajectory prediction model was established, and its parameters were optimized. Next, a tracking-training-testing algorithm was proposed for manipulator’s automatic moving target tracking, and the operating flows were detailed for training module, target detection module, and target tracking module. The proposed model and algorithm were proved effective through experiments.

Research on autonomous dynamic real-time capture of robot based on hybrid prediction model

“…Finally, the effectiveness of the prediction method is verified by simulation. In Luo, 14 the target trajectory prediction model is established based on LSTM, and its parameters are optimized to realize real-time tracking of the target by the robot in different scenarios. The target maneuvering trajectory prediction model based on PSR-RBF is established in Zhifei et al, 15 and the prediction model parameters are optimized LM and IPSO algorithms to improve the prediction performance of the target trajectory.…”