发表机构
Technical University of Munich; Professorship of Agrimechatronics; Munich Institute of Robotics and Machine Intelligence (MIRMI)（慕尼黑技术大学; 农业机电学教授职位; 慕尼黑机器人与机器智能研究所（MIRMI））
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究创建农用拖拉机数字孪生，以Mevea软件为基础、Python读写CAN消息，通过仿真与实际测试对比相似度，发现Mevea模型横向动力学表现佳，纵向需更好数据，为后续迭代纳入更多功能奠定基础。
AI 中文摘要
为提高研究效率和可用性，创建了研究用拖拉机（AMX G-trac）的数字孪生，特别关注遵循ISOBUS协议进行数据读取和执行命令的CAN通信。以Mevea仿真软件为基础，提供运动学模型和可视化，用Python通过Kvaser CanKing虚拟CAN通道读写CAN消息。在数字孪生仿真和现实世界中进行了直线和转弯行为等各种性能测试以测量相似度。结果表明，Mevea模型在横向动力学方面表现非常相似，通常在5%-10%以内，但需要更好的数据来完全捕捉纵向方面如加速度。本文描述的最终模型为第二轮迭代奠定了基础，以纳入更多拖拉机功能，如液压和拖拉机-农具动力学。
英文摘要
In efforts to increase research efficiency and availability, a digital twin of our research tractor (AMX G-trac) is created, focusing especially on the CAN communication for data reading and actuation command following the ISOBUS protocol. Mevea Simulation Software is utilized as the foundation, providing the kinematic model and visuals, while Python is used to read and write CAN messages over a Kvaser CanKing virtual CAN channel. Various performance tests involving straight line and turning behavior are performed in both the digital twin simulation and in the real world to measure similarity. Results indicate that the Mevea model behaves very comparable in its lateral dynamics, often within 5-10 percent, but requires better data to fully capture the longitudinal aspects like acceleration. The final model described in this paper sets the table for a second iteration to include more tractor functions such as hydraulics and tractor-implement dynamics.
Journal refTechnical University of Munich. 2026. ISBN 978-3-911430-17-3. https://mediatum.ub.tum.de/1858858
