一种基于语义分割和关键点检测的新型番茄采摘方法
A Novel Approach to Tomato Harvesting Using a Hybrid Gripper with Semantic Segmentation and Keypoint Detection
AI总结：
本文提出了一种结合语义分割和关键点检测的新型番茄采摘系统，通过混合机械手和智能控制实现高效、安全的采摘
摘要：
本文介绍了一种自主番茄采摘系统，该系统围绕一个混合机械手抓取器构建，结合六个柔软的仿生指和一个刚性的外骨骼以及一个橡胶篮子，以实现温和的笼状抓取。抓取器由伺服驱动的Scotch-yoke机制驱动，并包含分离叶片，形成一个圆台状结构以实现果实分离，同时集成微型伺服切割器用于茎部切割。在感知方面，RGB-D相机和基于Detectron2的管道执行对成熟/未成熟的番茄的语义分割以及在遮挡和光照变化下的茎部和果实中心的关键点定位。通过虚拟功原理推导出的分析模型将伺服扭矩与抓取力联系起来，使在设计层面能够推导出驱动需求。在执行过程中，通过比例-积分-微分控制器实现闭环抓取力调节，利用安装在选定手指上的力敏感电阻器反馈以防止滑动和损伤。运动执行由基于粒子群优化（PSO）的轨迹规划支持，用于5自由度机械臂。实验表明，能够完成完整的采摘循环（接近、分离、切割、抓取、运输、释放），平均循环时间为24.34秒，总体成功率为约80%，同时保持低的抓取力（0.20-0.50N）。这些结果验证了所提出的混合抓取器和集成视觉-控制管道在嘈杂环境中的可靠采摘性能。
英文摘要：
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.
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。
