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A Novel Approach to Tomato Harvesting Using a Hybrid Gripper with Semantic Segmentation and Keypoint Detection

2025-12-03 11:24:44
Shahid Ansari, Mahendra Kumar Gohil, Yusuke Maeda, Bishakh Bhattacharya

Abstract

This paper presents an autonomous tomato-harvesting system built around a hybrid robotic gripper that combines six soft auxetic fingers with a rigid exoskeleton and a latex basket to achieve gentle, cage-like grasping. The gripper is driven by a servo-actuated Scotch--yoke mechanism, and includes separator leaves that form a conical frustum for fruit isolation, with an integrated micro-servo cutter for pedicel cutting. For perception, an RGB--D camera and a Detectron2-based pipeline perform semantic segmentation of ripe/unripe tomatoes and keypoint localization of the pedicel and fruit center under occlusion and variable illumination. An analytical model derived using the principle of virtual work relates servo torque to grasp force, enabling design-level reasoning about actuation requirements. During execution, closed-loop grasp-force regulation is achieved using a proportional--integral--derivative controller with feedback from force-sensitive resistors mounted on selected fingers to prevent slip and bruising. Motion execution is supported by Particle Swarm Optimization (PSO)--based trajectory planning for a 5-DOF manipulator. Experiments demonstrate complete picking cycles (approach, separation, cutting, grasping, transport, release) with an average cycle time of 24.34~s and an overall success rate of approximately 80\%, while maintaining low grasp forces (0.20--0.50~N). These results validate the proposed hybrid gripper and integrated vision--control pipeline for reliable harvesting in cluttered environments.

Abstract (translated)

本文介绍了一种自主番茄采摘系统,该系统围绕一种混合型机器人夹爪构建而成,这种夹爪结合了六个软辅特异手指、刚性外骨骼和一个乳胶篮子,以实现温和的笼式抓取。夹爪通过伺服驱动的斯科奇-尤克机制进行操作,并包含分隔叶片形成圆锥台状结构用于水果隔离,以及集成微伺服切割器用于果柄切断。在感知方面,RGB-D相机和基于Detectron2的工作流程执行对成熟与未成熟番茄的语义分割,并在遮挡和光照变化下定位果柄和果实中心的关键点位置。利用虚功原理推导出分析模型,将伺服扭矩与抓取力联系起来,从而能够从设计层面理解驱动需求。在实际操作中,使用配备在选定手指上的力敏电阻反馈的PID控制器实现闭环抓握力调节,以防止滑动和擦伤。通过粒子群优化(PSO)轨迹规划支持五自由度机械臂的动作执行。实验表明,在平均周期时间为24.34秒的情况下,该系统可以完成完整的采摘循环(接近、分离、切割、抓取、运输、释放),整体成功率为约80%,同时保持较低的抓握力(0.20至0.50牛顿)。这些结果验证了所提出的混合夹爪及其集成视觉-控制管道在复杂环境中进行可靠收获的能力。

URL

https://arxiv.org/abs/2512.03684

PDF

https://arxiv.org/pdf/2512.03684.pdf


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