With recent advancements in industrial robots, educating students in new technologies and preparing them for the future is imperative. However, access to industrial robots for teaching poses challenges, such as the high cost of acquiring these robots, the safety of the operator and the robot, and complicated training material. This paper proposes two low-cost platforms built using open-source tools like Robot Operating System (ROS) and its latest version ROS 2 to help students learn and test algorithms on remotely connected industrial robots. Universal Robotics (UR5) arm and a custom mobile rover were deployed in different life-size testbeds, a greenhouse, and a warehouse to create an Autonomous Agricultural Harvester System (AAHS) and an Autonomous Warehouse Management System (AWMS). These platforms were deployed for a period of 7 months and were tested for their efficacy with 1,433 and 1,312 students, respectively. The hardware used in AAHS and AWMS was controlled remotely for 160 and 355 hours, respectively, by students over a period of 3 months.

翻译：随着工业机器人的最新进展，对学生进行新技术教育并为其未来做好准备变得至关重要。然而，在教学中使用工业机器人面临诸多挑战，例如购置成本高昂、操作人员与机器人自身的安全问题，以及复杂的培训材料。本文提出了两种利用开源工具（如机器人操作系统及其最新版本ROS 2）构建的低成本平台，旨在帮助学生通过远程连接的工业机器人学习和测试算法。研究团队将Universal Robotics（UR5）机械臂和定制移动漫游车部署于不同规模的测试环境（温室与仓库），分别构建了自主农业收割系统与自主仓库管理系统。这两个平台在为期7个月的部署期间，分别接受了1,433名和1,312名学生的有效性测试。在3个月周期内，学生通过远程控制方式分别操作AAHS和AWMS硬件系统达160小时和355小时。