Wearable Data Glove Design Based on Strain Sensors for Bionic Manipulator Control

To address the challenges associated with remote manipulation in complex environments, this study presents a remote control system for bionic manipulators utilizing a strain-sensor-based data glove. The system captures joint angle data from five-finger grasps and thumb-index opposition gestures, which are then processed through limit filtering, Kalman filtering, and range mapping to improve control robustness. A vibration feedback module delivers tactile force information from the bionic fingers back to the user’s hand, enhancing grip accuracy and preventing structural damage caused by excessive manipulator motion. Experimental results confirm that the data glove enables reliable remote control of the bionic hand when handling fragile objects, thereby validating the system’s effectiveness and precision.