无需触觉反馈，用双层框架实现灵巧手精准抓握易损物体
Rigidity-Based Multi-Finger Coordination for Precise In-Hand Manipulation of Force-Sensitive Objects
- 基于图刚度与力封闭约束规划多指协同受力
- 在自研灵巧手上成功操控软线、塑料杯、生鸡蛋等脆弱物
- 适合缺乏触觉传感器的商用灵巧手场景
精确操控力敏感物体通常需要精心协调的力规划以及准确的接触力反馈与控制。与带有夹持末端执行器的多臂平台不同，多指灵巧手仅依赖指尖点接触且无法施加拉力，因而面临更大挑战。此外，大多数商用灵巧手中缺乏校准的扭矩传感器，进一步增加了难度。为解决这些问题，我们提出一种双层多指协调框架，通过关节控制实现无触觉反馈下的高精度操作。该方法结合图刚度与力封闭约束求解协同接触力规划，并通过力到位置映射将规划的力轨迹转化为关节轨迹。我们在自研灵巧手上验证了该框架，成功实现了对脆弱物体——包括软线、塑料杯和生鸡蛋——的高精度、高安全性操控。
原文摘要 · Abstract (English)
Precise in-hand manipulation of force-sensitive objects typically requires judicious coordinated force planning as well as accurate contact force feedback and control. Unlike multi-arm platforms with gripper end effectors, multi-fingered hands rely solely on fingertip point contacts and are not able to apply pull forces, therefore poses a more challenging problem. Furthermore, calibrated torque sensors are lacking in most commercial dexterous hands, adding to the difficulty. To address these challenges, we propose a dual-layer framework for multi-finger coordination, enabling high-precision manipulation of force-sensitive objects through joint control without tactile feedback. This approach solves coordinated contact force planning by incorporating graph rigidity and force closure constraints. By employing a force-to-position mapping, the planned force trajectory is converted to a joint trajectory. We validate the framework on a custom dexterous hand, demonstrating the capability to manipulate fragile objects-including a soft yarn, a plastic cup, and a raw egg-with high precision and safety.
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