低成本压力传感器助力机器人精准抓取易损果蔬
Efficient Force and Stiffness Prediction in Robotic Produce Handling with a Piezoresistive Pressure Sensor
- 用柔性压阻传感器实时感知抓握力与物体刚度
- 算法加速估算稳态值，支持实时反馈控制
- 可识别果蔬成熟度与损伤，适合农业分拣场景
用机器人处理易损农产品是未来农业自动化的重要环节。正确控制抓握力不仅能确保稳定抓取，还能避免产品损坏或碰伤。本文集成了一种低成本、易制造的柔性压力传感器到机械夹爪中，适用于不同形状、大小和刚度的农产品。该传感器成功应用于刚性夹爪和气动软指两种结构。同时提出一种基于瞬态响应数据的快速稳态值估计算法，支持实时应用。实验表明，传感器能有效反馈信息，实现对未知尺寸和刚度物体的正确抓取；同时可提供物体刚度和受力估计，用于判断成熟度和损伤情况。该系统还具备对变刚度物体的力反馈能力，为后续的品质检测、按成熟度分选等任务提供了可能。
原文摘要 · Abstract (English)
Properly handling delicate produce with robotic manipulators is a major part of the future role of automation in agricultural harvesting and processing. Grasping with the correct amount of force is crucial in not only ensuring proper grip on the object, but also to avoid damaging or bruising the product. In this work, a flexible pressure sensor that is both low cost and easy to fabricate is integrated with robotic grippers for working with produce of varying shapes, sizes, and stiffnesses. The sensor is successfully integrated with both a rigid robotic gripper, as well as a pneumatically actuated soft finger. Furthermore, an algorithm is proposed for accelerated estimation of the steady-state value of the sensor output based on the transient response data, to enable real-time applications. The sensor is shown to be effective in incorporating feedback to correctly grasp objects of unknown sizes and stiffnesses. At the same time, the sensor provides estimates for these values which can be utilized for identification of qualities such as ripeness levels and bruising. It is also shown to be able to provide force feedback for objects of variable stiffnesses. This enables future use not only for produce identification, but also for tasks such as quality control and selective distribution based on ripeness levels.
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