We introduce RAMP, an open-source robotics benchmark inspired by real-world industrial assembly tasks. RAMP consists of beams that a robot must assemble into specified goal configurations using pegs as fasteners. As such, it assesses planning and execution capabilities, and poses challenges in perception, reasoning, manipulation, diagnostics, fault recovery, and goal parsing. RAMP has been designed to be accessible and extensible. Parts are either 3D printed or otherwise constructed from materials that are readily obtainable. The design of parts and detailed instructions are publicly available. In order to broaden community engagement, RAMP incorporates fixtures such as April Tags which enable researchers to focus on individual sub-tasks of the assembly challenge if desired. We provide a full digital twin as well as rudimentary baselines to enable rapid progress. Our vision is for RAMP to form the substrate for a community-driven endeavour that evolves as capability matures.

翻译：我们提出RAMP，一个受真实工业装配任务启发的开源机器人基准测试平台。该平台包含一系列横梁，机器人需使用销钉作为紧固件将其组装成指定目标构型。该基准测试体系评估了规划与执行能力，并涉及感知、推理、操作、诊断、故障恢复及目标解析等多方面挑战。RAMP的设计注重可访问性与可扩展性：组件可通过3D打印或常见材料制作，零部件设计图及详细操作说明均已公开。为促进社区参与，RAMP集成了April Tag等定位标记，使研究者可聚焦于装配挑战中的特定子任务。我们提供了完整的数字孪生系统及基础基线方法以加速研究进程。我们的愿景是让RAMP成为社区驱动的演化平台，随技术成熟度持续发展。