用数字孪生实现实时控制软体夹爪，精度高且适配工业场景。
A Novel Approach to Grasping Control of Soft Robotic Grippers based on Digital Twin
- 基于视觉与运动学建模，在Unity中模拟夹爪形变。
- 通过图像处理与数据拟合建立压力-形变映射关系。
- 适合需高精度实时控制的工业自动化应用。
本文提出一种基于数字孪生（Digital Twin, DT）框架，实现软体机械手在实时运动与姿态控制中的应用。该数字孪生系统依托工业机器人工作站，结合我们新提出的软体夹爪控制方法，主要基于计算机视觉技术，实时设定驱动压力以达到期望的夹爪状态。通过四段式恒曲率运动学模型，在Unity 3D中模拟夹爪运动，计算其参数（如曲率、弯曲角度等）。利用基于OpenCV的图像处理算法与数据拟合，实现驱动压力与夹爪形态之间的映射。实验结果表明，该数字孪生方法在软体夹爪操作的实时控制中表现良好，可满足多种工业应用场景的需求。
原文摘要 · Abstract (English)
This paper has proposed a Digital Twin (DT) framework for real-time motion and pose control of soft robotic grippers. The developed DT is based on an industrial robot workstation, integrated with our newly proposed approach for soft gripper control, primarily based on computer vision, for setting the driving pressure for desired gripper status in real-time. Knowing the gripper motion, the gripper parameters (e.g. curvatures and bending angles, etc.) are simulated by kinematics modelling in Unity 3D, which is based on four-piecewise constant curvature kinematics. The mapping in between the driving pressure and gripper parameters is achieved by implementing OpenCV based image processing algorithms and data fitting. Results show that our DT-based approach can achieve satisfactory performance in real-time control of soft gripper manipulation, which can satisfy a wide range of industrial applications.
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