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Deformable Cargo Transport in Microgravity with Astrobee

Daniel Morton, Rika Antonova, Brian Coltin, Marco Pavone, Jeannette Bohg

TL;DR

This work addresses autonomous cargo transport of deformable bags in microgravity, focusing on the Astrobee platform. It introduces pyastrobee, a Python-based simulation, planning, modeling, and control stack, and demonstrates a sampling-based MPC that uses reduced-order CTB models to steer a high-order FEM bag via simulation. The results show preliminary success in transferring cargo through ISS module corridors while avoiding collisions. The project is open-source, well-documented, and aims to advance autonomous space-robotics manipulation, planning, and control research.

Abstract

We present pyastrobee: a simulation environment and control stack for Astrobee in Python, with an emphasis on cargo manipulation and transport tasks. We also demonstrate preliminary success from a sampling-based MPC controller, using reduced-order models of NASA's cargo transfer bag (CTB) to control a high-order deformable finite element model. Our code is open-source, fully documented, and available at https://danielpmorton.github.io/pyastrobee

Deformable Cargo Transport in Microgravity with Astrobee

TL;DR

This work addresses autonomous cargo transport of deformable bags in microgravity, focusing on the Astrobee platform. It introduces pyastrobee, a Python-based simulation, planning, modeling, and control stack, and demonstrates a sampling-based MPC that uses reduced-order CTB models to steer a high-order FEM bag via simulation. The results show preliminary success in transferring cargo through ISS module corridors while avoiding collisions. The project is open-source, well-documented, and aims to advance autonomous space-robotics manipulation, planning, and control research.

Abstract

We present pyastrobee: a simulation environment and control stack for Astrobee in Python, with an emphasis on cargo manipulation and transport tasks. We also demonstrate preliminary success from a sampling-based MPC controller, using reduced-order models of NASA's cargo transfer bag (CTB) to control a high-order deformable finite element model. Our code is open-source, fully documented, and available at https://danielpmorton.github.io/pyastrobee
Paper Structure (7 sections, 4 figures)

This paper contains 7 sections, 4 figures.

Table of Contents

  1. Introduction
  2. Simulation Environment
  3. Planning
  4. Cargo Modeling
  5. Control
  6. Conclusion
  7. Acknowledgments

Figures (4)

  • Figure 1: The ISS environment. We build on NASA's high-quality meshes and textures for the ISS (left), and additionally provide an approximate convex-decomposition collision representation for each module (right)
  • Figure 2: Trajectory planning and tracking. Left: The global planner provides minimum-jerk trajectories (white) through the convex-corridor safe set (red). Right: a snapshot of Astrobee tracking a reference plan with the provided PD tracking controller.
  • Figure 3: Modeling deformable cargo. We provide models of the deformable cargo of varying fidelity, including a finite-element deformable bag (A), soft-constraint-handle bag (B), composite-body bag (C), and a URDF model (D), as shown with their wireframe views. Additional models are provided for different handle locations, and multiple handles (for multi-robot manipulation).
  • Figure 4: Controlling the cargo transport task. Our preliminary sampling-based MPC stabilizes the system while transporting the bag through a tight corridor between the Node 2 and JEM modules, without collision.