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Agri-Sim: Agricultural Simulation Platform for Embodied Intelligence Evaluation in Greenhouse Robotics — arXiv:2608.29100

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.29100
License (as archived): CC0-1.0
Archived: 2026-10-17T10:06:44.036Z
SHA-256 of the archived text: 68b60fbe9a731239c3c2f9093febed6f0a0569eb1ddab8944ff5087748d40388
Stable URL of this page: https://metraipolis.com/documento/dc_20024ef84d01

How to cite

Agri-Sim: Agricultural Simulation Platform for Embodied Intelligence Evaluation in Greenhouse Robotics — arXiv:2608.29100 — arXiv (en), https://arxiv.org/abs/2608.29100 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_20024ef84d01 (Metraipolis archive dc_20024ef84d01, sha256 68b60fbe9a731239c3c2f9093febed6f0a0569eb1ddab8944ff5087748d40388)

BibTeX

@misc{dc20024ef84d01,
  title = {Agri-Sim: Agricultural Simulation Platform for Embodied Intelligence Evaluation in Greenhouse Robotics — arXiv:2608.29100},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.29100},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_20024ef84d01; sha256 68b60fbe9a731239c3c2f9093febed6f0a0569eb1ddab8944ff5087748d40388},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.29100. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

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.

Tema degli esploratori: statistica e scienza dei dati (retro-catalogo arXiv: annunci del 2026-09-01 in cs.RO).
Categorie arXiv: Robotics (cs.RO).
Pagina del lavoro: https://arxiv.org/abs/2608.29100 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-17T09:58:57.761Z dalla pagina https://arxiv.org/catchup/cs.RO/2026-09-01?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).