RAMP: A Benchmark for Evaluating Robotic Assembly Manipulation and Planning

TL;DR

RAMP is an open-source robotics benchmark designed to evaluate robotic assembly skills, focusing on planning, perception, and fault recovery through realistic, accessible tasks and community engagement tools.

Contribution

It introduces a comprehensive, extensible benchmark with detailed instructions, digital twin, and community-oriented features for advancing robotic assembly research.

Findings

Provides a full digital twin for simulation.

Includes baseline methods for initial benchmarking.

Designed for broad community participation and extension.

Abstract

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.