用视觉感知避免软夹爪抓圆柱物时碰撞，实现稳定抓取。
A Vision-Based Collision Sensing Method for Stable Circular Object Grasping with A Soft Gripper System
- 通过眼在手上相机实时监测手指与物体运动
- 碰撞响应时间瞬时，能精准识别碰撞方向和大小
- 适合需要高精度动态抓取的柔性机器人系统
机器人执行器外部碰撞常导致圆柱形物体抓取失败。本文提出一种基于视觉的碰撞感知模块，可配合软夹爪系统维持稳定抓取。系统采用广视角眼在手上相机，同步监控夹爪手指与被抓物体的运动状态。此外，设计了一种富含碰撞应对策略的抓取方法，确保整个动态抓取过程的稳定性与安全性。制作了物理软夹爪并安装于协作机械臂上，用于评估碰撞检测机制性能。实验验证了该机制具备瞬时响应能力。避让测试表明，夹爪能精确感知外部碰撞的方向与强度。
原文摘要 · Abstract (English)
External collisions to robot actuators typically pose risks to grasping circular objects. This work presents a vision-based sensing module capable of detecting collisions to maintain stable grasping with a soft gripper system. The system employs an eye-in-palm camera with a broad field of view to simultaneously monitor the motion of fingers and the grasped object. Furthermore, we have developed a collision-rich grasping strategy to ensure the stability and security of the entire dynamic grasping process. A physical soft gripper was manufactured and affixed to a collaborative robotic arm to evaluate the performance of the collision detection mechanism. An experiment regarding testing the response time of the mechanism confirmed the system has the capability to react to the collision instantaneously. A dodging test was conducted to demonstrate the gripper can detect the direction and scale of external collisions precisely.
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