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.

翻译：在农业收获与加工领域，机器人操作器妥善处理易损农产品是未来自动化应用的重要组成部分。施加恰当的抓取力不仅对确保物体稳固抓持至关重要，也能避免对产品造成损伤或瘀伤。本研究将一种低成本、易制造的柔性压力传感器集成于机器人夹爪，用于处理不同形状、尺寸和刚度的农产品。该传感器成功集成于刚性机器人夹爪及气动驱动的软体手指。此外，本文提出一种基于瞬态响应数据加速估计传感器输出稳态值的算法，以实现实时应用。实验证明该传感器能有效融合反馈信息以正确抓取未知尺寸与刚度的物体。同时，传感器提供的参数估计值可用于识别成熟度、瘀伤等品质特征。研究还表明该传感器能为变刚度物体提供力反馈。这为未来不仅应用于农产品识别，还可拓展至基于成熟度的质量控制和分级分选等任务奠定了基础。