发表机构
School of Mechatronic Engineering and Automation, Shanghai University; Sino-European School of Technology of Shanghai University; School of Future Technology (Institute of Artificial Intelligence), Shanghai University（上海大学机电工程与自动化学院; 上海大学中欧工程技术学院; 上海大学未来技术学院（人工智能研究院））
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究针对农业机器人开发所需的仿真环境需求，提出基于Unity和ROS2的Agri-Sim平台，通过实验验证其可支持导航与操纵工作流的闭环集成及可重复功能评估，为后续相关研究提供实用基础。
AI 中文摘要
农业机器人的开发需要能够共同支持真实场景构建、虚拟传感、自主导航、运动规划及操纵任务执行的仿真环境。本文提出Agri-Sim，这是一个基于Unity和ROS2的仿真平台，用于农业机器人的闭环开发与功能评估。该平台包含可配置的番茄温室环境、移动双臂收获机器人、虚拟RGB-D、LiDAR、IMU及关节传感器，以及Unity与ROS2之间的双向通信接口。Unity负责场景渲染、刚体动力学、碰撞检测、虚拟传感及任务状态执行，而ROS2与MoveIt 2提供定位、导航、碰撞感知运动规划、逆运动学及轨迹生成。采用自主温室导航与双臂番茄收获来评估完整的仿真工作流，实验涵盖虚拟传感器发布、基于ROS2的导航、碰撞感知运动规划、移动基座控制、番茄获取、臂间交接及装箱放置。结果表明，Agri-Sim支持受控虚拟温室中导航与操纵工作流的闭环集成及可重复功能评估，为后续算法开发与仿真到现实（Sim-to-Real）研究提供了实用基础。
英文摘要
Agricultural-robot development requires simulation environments that can jointly support realistic scene construction, virtual sensing, autonomous navigation, motion planning, and manipulation-task execution. This paper presents Agri-Sim, a Unity and ROS2-based simulation platform for the closed-loop development and functional evaluation of agricultural robots. The platform contains a configurable tomato-greenhouse environment, a mobile dual-arm harvesting robot, virtual RGB-D, LiDAR, IMU, and joint sensors, and a bidirectional communication interface between Unity and ROS2. Unity is responsible for scene rendering, rigid-body dynamics, collision detection, virtual sensing, and task-state execution, whereas ROS2 and MoveIt 2 provide localization, navigation, collision-aware motion planning, inverse kinematics, and trajectory generation. Autonomous greenhouse navigation and dual-arm tomato harvesting were used to evaluate the complete simulation workflow. The experiments covered virtual sensor publication, ROS2-based navigation, collision-aware motion planning, mobile-base control, tomato acquisition, inter-arm handover, and box placement. The results demonstrate that Agri-Sim supports closed-loop integration and repeatable functional evaluation of navigation and manipulation workflows in a controlled virtual greenhouse, providing a practical foundation for subsequent algorithm development and Sim-to-Real studies.
Comments13 pages, 9 figures, and 5 tables
