Simulation framework mjorbit enables realistic space robot testing
mjorbit: A Simulation Framework for Space Robotics
Robotics
Summary
Simulating robots that work in space is complicated because they move in orbit and interact with other objects. This paper introduces mjorbit, a software tool that combines space physics with robot simulation to model multi-part space robots realistically. The authors tested mjorbit on practical scenarios like space servicing and assembly, using advanced control methods. Their framework runs efficiently on different computer systems and is available as open-source for others to try.
space roboticsrobot simulationorbit propagationmulti-body dynamicsMuJoCo enginemodel-predictive controlreinforcement learningspacecraft actuatorsGPU computingopen-source software
Authors
John Z. Zhang, Joris Verhagen, Fausto Vega, Patrick McKeen, Zachary Manchester
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/