Real-Time 3-D Force Measurements Using Vision-Based Flexible Force Sensor

This article presents the design and application of a vision-based flexible 3-D force sensor, specifically designed for force measurement in the field of instrument measurement. The sensor utilizes visual information, employing highly elastic silicone as the contact surface and continuous marker patterns as the visual data source. By integrating a vision system, the sensor captures image data and relies on a novel deep learning model to achieve precise measurements of 3-D forces. Experimental evaluation was conducted to assess the sensor’s performance, demonstrating its exceptional fitting performance with a minimum mean squared error of 0.15 N. Moreover, the flexible sensor exhibits excellent real-time decoupling capabilities for 3-D forces at a frequency rate of 30 Hz for three orthogonal force components. We embedded the sensor into a mechanical gripper and successfully achieved self-adaptive force grasping, verifying its effectiveness in accurately measuring 3-D forces in the instrument measurement environment. The proposed vision-based flexible 3-D force sensor presents an innovative solution for force sensing applications in robotics and related fields. Its compact design, high fitting performance, and real-time decoupling capabilities make it a valuable tool for enhancing the accuracy and versatility of force sensing systems in various practical instrument measurement scenarios.