构建可闭环评估温室机器人的仿真平台，支持真实场景与自主作业测试。
Agri-Sim: Agricultural Simulation Platform for Embodied Intelligence Evaluation in Greenhouse Robotics
- 基于Unity与ROS2构建闭环仿真系统，集成虚拟感知与运动规划。
- 实现移动双臂番茄采摘全流程，涵盖导航、避障、抓取与交接动作。
- 适合农业机器人算法开发与真实世界迁移研究者使用。
农业机器人研发需要能够同时支持真实场景构建、虚拟传感、自主导航、运动规划和操作任务执行的仿真环境。本文提出Agri-Sim，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。平台包含可配置的番茄温室环境、带双机械臂的移动采摘机器人、虚拟的RGB-D、LiDAR、IMU和关节传感器，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、虚拟传感和任务状态执行；ROS2与MoveIt 2则提供定位、导航、避障运动规划、逆运动学和轨迹生成。通过自主温室导航与双臂番茄采摘实验，验证了完整的仿真工作流。实验覆盖虚拟传感器发布、ROS2导航、避障运动规划、移动基座控制、番茄获取、双臂交接及箱体放置等环节。结果表明，Agri-Sim支持在受控虚拟温室中对导航与操作流程进行闭环集成与可重复的功能评估，为后续算法开发与从仿真到现实的迁移研究提供了实用基础。
原文摘要 · Abstract (English)
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.
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