mlsanityData to 14 Oct 2026

Crossing the Sim2Real Gap Between Simulation and Ground Testing to Space Deployment of Autonomous Free-flyer Control

arXiv 2512.03736 ↗First posted 3 Dec 2025cs.RO cs.LG cs.SYcited by 0

On the map: Deep reinforcement learning methods → RL for robot navigation and UAV control

Abstract (arXiv)

Reinforcement learning (RL) offers transformative potential for robotic control in space. We present the first on-orbit demonstration of RL-based autonomous control of a free-flying robot, the NASA Astrobee, aboard the International Space Station (ISS). Using NVIDIA's Omniverse physics simulator and curriculum learning, we trained a deep neural network to replace Astrobee's standard attitude and translation control, enabling it to navigate in microgravity. Our results validate a novel training pipeline that bridges the simulation-to-reality (Sim2Real) gap, utilizing a GPU-accelerated, scientific-grade simulation environment for efficient Monte Carlo RL training. This successful deployment demonstrates the feasibility of training RL policies terrestrially and transferring them to space-based applications. This paves the way for future work in In-Space Servicing, Assembly, and Manufacturing (ISAM), enabling rapid on-orbit adaptation to dynamic mission requirements.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in RL for robot navigation and UAV control, one of 15 directions in Deep reinforcement learning methods. Builds on 8 of its 28 references that are in the map. First posted on arXiv 3 Dec 2025.

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8 of 28 references.

References · 8

  1. 2017Proximal Policy Optimization Algorithmscited by 15,215
  2. 2015High-Dimensional Continuous Control Using Generalized Advantage Estimationcited by 2,026
  3. 2018Learning Dexterous In-Hand Manipulationcited by 687
  4. 2021Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learningcited by 512
  5. 2020Curriculum Learning for Reinforcement Learning Domains: A Framework and Surveycited by 373
  6. 2023Orbit: A Unified Simulation Framework for Interactive Robot Learning Environmentscited by 295
  7. 2023RANS: Highly-Parallelised Simulator for Reinforcement Learning based Autonomous Navigating Spacecraftscited by 6
  8. 2024PPO-based Dynamic Control of Uncertain Floating Platforms in the Zero-G Environmentcited by 4

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  1. 2025Autonomous Planning In-space Assembly Reinforcement-learning free-flYer (APIARY) International Space Station Astrobee Testing
  2. 2025Space Robotics Bench: Robot Learning Beyond Earth
  3. 2025RL-AVIST: Reinforcement Learning for Autonomous Visual Inspection of Space Targets
  4. 2026Deep Reinforcement Learning for Spacecraft Attitude Control During Atmospheric Re-Entry
  5. 2025Reinforcement Learning based 6-DoF Maneuvers for Microgravity Intravehicular Docking: A Simulation Study with Int-Ball2 in ISS-JEM
  6. 2025LeLaR: The First In-Orbit Demonstration of an AI-Based Satellite Attitude Controller
  7. 2025Deep Reinforcement Learning Policies for Underactuated Satellite Attitude Control
  8. 2025OrbitZoo: Real Orbital Systems Challenges for Reinforcement Learning