Papers for

robotics algorithm developers

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Efficient simulation framework brings advanced robotics to space operations

mjorbit: A Simulation Framework for Space Robotics

Abstract: This paper presents a general framework for simulating multi-body space robots with contact. We bring efficient, large-scale robot simulation to in-space servicing, assembly, and manufacturing applications. First, we perform an empirical trade study of methods for coupling orbit propagation with existing robotics simulation frameworks. Next, we present mjorbit, a general, flexible, and performant framework built on the MuJoCo engine widely used in robotics, to which we add key spacecraft dynamics, actuators, and sensors. We provide a low-latency C++ CPU backend and a high-throughput GPU backend behind a simple Python API. We demonstrate mjorbit by solving several realistic on-orbit case studies with both model-predictive control and reinforcement learning. Open-source code and examples are available at: https://johnzhang3.github.io/mjorbit/

Mon 7 SeptRobotics
The gist
Simulating robots in space is hard because they move around large, complex machines in weightless environments. The authors studied different ways to combine space movement with robot simulation. They made a new tool called mjorbit, which uses an existing robot simulator but adds space-specific physics and parts. They show how this tool can help control robots working on satellites or space stations using advanced methods like predictive control and learning. The tool and examples are available for anyone to use.
Open → 2609.08010v1