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.
@article{arxiv.2305.09644,
title = {RAMP: A Benchmark for Evaluating Robotic Assembly Manipulation and Planning},
author = {Jack Collins and Mark Robson and Jun Yamada and Mohan Sridharan and Karol Janik and Ingmar Posner},
journal= {arXiv preprint arXiv:2305.09644},
year = {2023}
}