Research On Power Line Maintenance Manipulator Control Based On Gesture Recognition Technology

The current wide application of intelligent equipment in various fields of life,intelligent equipment has replaced the traditional manual operation has become a hot research topic.Remotely operated robots operate in the inability of humans to reach or inconvenience,and have an indelible effect on the development of modern industry and the improvement of work efficiency.The multi-sensor fusion based gesture recognition technology studied in this paper combines manipulator operation and gesture recognition to realize the synchronous movement of the human hand and the robot,and can operate the robot for simple mechanical maintenance.The main contents of this paper are as follows:(1)the overall system analysis of the gesture recognition technology control manipulator,introduces the principle of gesture recognition,man-to-manipulator mapping and the overall control system;(2)solves the attitude angle around the gesture posture: constructs the gesture The motion system controls the motion information of the manipulator,and solves the acquired gesture data information by the quaternion method to obtain the accurate position of the robot movement,so that the accuracy of the gesture recognition is significantly improved;(3)the gesture data fusion filtering process: The hand movement and motion trajectory analysis are used to analyze and process the gesture data.In order to respond more promptly to the change of human hand movement state and obtain more stable and accurate human hand data information,an improved based on the “current statistics” model adaptive Kalman filter algorithm for filtering and trajectory tracking;(4)robot control system implementation and experimental analysis: a brief analysis from hardware and software,respectively,using the neural network learning factor to train the controlrecognition of the robot,which is conducive to improve the system Stable Qualitative and adaptable;in the experimental debugging,the operation process of the experimental equipment is introduced in detail,and the robot can achieve the preset experimental results better.The main technical characteristics of this paper are as follows:(1)combining gesture and pose transformation with matrix transformation,constructing gesture motion system,defining gesture attitude angle,and solving gesture gesture;(2)combining kinematics,adopting improved based on current The model Kalman filtering method is used to process the gesture data;(3)the neural network is added to train the robot movement.After theoretical analysis and experimental verification,the gesture angle and the filtered gesture data after verification are verified to improve the stability of the gesture data and improve the intelligent level of human-computer interaction.