基于力传感器的采摘模式分析与两指爪设计——面向温室樱桃番茄机器人采摘
Force Sensor-Based Picking Pattern Analysis and Two-Jaw Gripper Design for Cherry Tomato Robotic Harvesting in Greenhouse
AI总结：
本研究提出力数据驱动的樱桃番茄机器人采摘框架，通过分析三种采摘模式的力/力矩特征设计Finray夹爪，在温室试验中实现86.0%采摘成功率，性能优于多种传统末端执行器。
摘要：
温室樱桃番茄的机器人采摘仍面临诸多挑战，包括果实簇密集、果皮娇嫩，以及需要轻柔且有效的分离方式。本研究提出一种力数据驱动的自主樱桃番茄采摘框架，集成了六轴力/力矩传感、仿生柔顺夹爪，并部署于移动机器人平台。在实验室和温室环境中，通过安装在食指上的可穿戴ATI六轴力/力矩传感器，采集了150次人工试验（每种采摘模式各50次）中三种基础采摘模式（夹持、扭转、侧向拉动）的动力学特征：夹持所需的峰值法向力为3.92 N和0.45 N；扭转在果梗轴上产生的主导力矩为19.20±2.10 N·mm，且对果梗支架的干扰极小；单纯侧向拉动不足以实现可靠分离。这些测量结果为新型指尖定位Finray夹爪的设计提供了依据，该夹爪的果实接触区域采用柔顺TPU 95A Finray几何结构，主体采用刚性PLA材质，模拟人类指尖的双刚度特性。采用基于电流的力矩控制的Dynamixel XM430-W350伺服电机，施加测得的夹持力和45°腕部扭转。有限元分析显示，在3.92 N载荷下最大冯·米塞斯应力为0.24 MPa，低于樱桃番茄果皮的损伤阈值。该系统集成在UR5机械臂和Clearpath Husky A200底盘上，在NVIDIA Isaac Sim中进行了验证，并在阿联酋阿布扎比SILAL商业温室完成了50次自主试验。混合夹持-扭转-拉动策略实现了86.0%的采摘成功率、2.3%的果实损伤率和单果8.4秒的周期时间，优于真空（66.3%）、旋转（70.1%）、夹持（76.0%）和吸切（52.4%）末端执行器。这些结果证明了在测试设施和品种条件下的初步可行性。
英文摘要：
Robotic harvesting of cherry tomatoes in greenhouses remains challenging due to dense fruit clusters, delicate skin, and the need for gentle yet effective detachment. This study presents a force-data-driven framework for autonomous cherry tomato harvesting that integrates six-axis force/torque sensing, a bio-inspired compliant gripper, and deployment on a mobile robotic platform. A wearable ATI six-axis force/torque sensor mounted on the index finger captured kinetic signatures of three elemental picking patterns (gripping, twisting, and lateral pulling) across 150 manual trials (50 per pattern) in laboratory and greenhouse settings. Gripping required a peak normal force of 3.92 and 0.45 N, twisting produced a dominant torque of 19.20 2.10 Nmm about the pedicel axis with minimal truss disturbance, and pure lateral pulling alone was insufficient for reliable detachment. These measurements informed a novel fingertip-localised Finray gripper, with compliant TPU 95A Finray geometry restricted to the fruit-contact region and a rigid PLA body, emulating the dual-stiffness human fingertip. A Dynamixel XM430-W350 servomotor under current-based torque control applies the measured gripping force and a 45° wrist twist. Finite element analysis showed a maximum von Mises stress of 0.24 MPa under the 3.92 N load, below the bruising threshold of cherry tomato skin. Integrated on a UR5 arm and Clearpath Husky A200 base, the system was validated in NVIDIA Isaac Sim and in 50 autonomous trials at the SILAL commercial greenhouse, Abu Dhabi, UAE. The hybrid grip-twist-pull strategy achieved an 86.0% picking success rate, 2.3% fruit damage, and an 8.4 s cycle time per fruit, outperforming vacuum (66.3%), rotating (70.1%), clamping (76.0%), and suction-cutting (52.4%) end-effectors. These results demonstrate preliminary feasibility under the tested facility and cultivar conditions
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
