Design of material handling robot based on LSTM+DTW algorithm

For the sake of satisfying the needs of material handling in intelligent logistics warehouses and industrial buildings better and improving the deficiencies of existing material handling forms, in this paper, we design an intelligent material handling robot servo system that integrates DTW (Dynamic time warping) and LSTM (Long Short Term Memory) algorithms. The operator can command the robot to move in multiple directions according to the motion intention of the human body through the human manipulative mode based on the hand movement or the rod traction mode with weak traction. This project collects various motion pattern data through experiments. After preprocessing the data, features are extracted and repeated motion pattern recognition training and template matching are carried out to deeply learn and perceive human intention. We input the data collected in real time into the generated LSTM network model, identify the motion pattern in real time, and introduce the DTW algorithm for template matching verification. Through testing, the accuracy of motion pattern recognition can exceed 95% under the effective combination of the two algorithms, which is higher than that of the DTW and LSTM algorithms.