Automatic control technology of mechanical equipment based on microelectronic sensing signal control

The purpose of the research is to implement a master-slave control system for hand virtual-real interaction, which can capture the position, direction and finger joint angle of the user’s hand in real-time. After being analyzed, the original mot analyzed goes through limiting and removing joggle procedures, integrating the complementary filter algorithm and obtaining a drive database based on the Kalman filter algorithm. The data is used to drive the virtual hand to interact with the virtual environment, with the Roll, Pitch and Yaw being ±0.1∘, ±0.15∘, ±0.15∘, respectively.These data prove that the data processing algorithm is compatible with the system hardware platform regarding accuracy and noise reduction. In the process of building the virtual model, under the premise of satisfying a certain number of meshes, the texture mapping of the hand model not only satisfies the fidelity of the virtual hand model but also makes the model less complex and interactive. This helped solve the fragile joint connection problem when the finger was bent. In the subsequent interaction experiment, the system was tested with static gestures and dynamic grasping, and the experimental data and interaction effect showed that the system had good interactivity and stability.