Enhancing Dynamic Simulations with Mass Properties for In-Space Autonomous Robotic Systems

Background: In-Space Servicing, Assembly, and Manufacturing (ISAM) is pivotal to NASA’s pursuit of an extended human presence outside of Earth. Space structures increasingly surpass payload capacities of current and anticipated launch vehicles. High precision robotic systems, capable of autonomous assembly and maintaining complex structures, provide a potential solution for this limitation.

Purpose/Objectives: The objective of Precision Assembled Space Structures (PASS) is to demonstrate autonomous modular assembly of a 20-meter diameter primary mirror backbone structure for an In-Space Assembled Telescope. Development and validation of critical technologies is key for high-accuracy, high- efficiency, on-orbit assembly operations.

Methods: Successful robotic operation requires exhaustive testing. Simulations provide a controlled environment to model robotic behaviors. PASS utilizes tools including URDFs (Unified Robot Description Format), ROS2, Gazebo, Python, and C++ to emulate robotic systems and environmental contexts. This project focused on integrating accurate mass properties to enhance dynamic simulation fidelity. The process included identifying methodologies to handle equations of motion, functional verification, and program integration.

Key Results: Several candidate programming libraries were examined for their usability, capability, and compatibility. PyBullet met all criteria and was capable of parsing URDFs, importing robots by URDF, and calculating dynamic equations. Functionality was verified against URDFs and produced correct mass matrices. PyBullet demonstrated interoperability with the existing PASS framework, displaying URDF compatibility and ease of importation. Other libraries exhibited point mass properties, complicated onboardings, or sparse documentation.

Conclusions: This research has the potential to realize large-scale, ambitious space structures but also paves the way for broader applications of in-space robotic assembly.