mlsanityData to 7 Oct 2026

Sim-to-(Multi)-Real: Transfer of Low-Level Robust Control Policies to Multiple Quadrotors

arXiv 1903.04628 ↗First posted 11 Mar 2019cs.ROcited by 36

Not on the map. Why?

Abstract (arXiv)

Quadrotor stabilizing controllers often require careful, model-specific tuning for safe operation. We use reinforcement learning to train policies in simulation that transfer remarkably well to multiple different physical quadrotors. Our policies are low-level, i.e., we map the rotorcrafts' state directly to the motor outputs. The trained control policies are very robust to external disturbances and can withstand harsh initial conditions such as throws. We show how different training methodologies (change of the cost function, modeling of noise, use of domain randomization) might affect flight performance. To the best of our knowledge, this is the first work that demonstrates that a simple neural network can learn a robust stabilizing low-level quadrotor controller (without the use of a stabilizing PD controller) that is shown to generalize to multiple quadrotors.

Key facts. Cited by 36 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Mar 2019.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 7; 2022: 4; 2023: 11; 2024: 6; 2025: 7; 2026: 1.

36 papers.

Sort:

By area:

  1. 2024Deep Reinforcement Learning for Robotics: A Survey of Real-World Successescited by 153
  2. 2021Learning to Fly -- a Gym Environment with PyBullet Physics for Reinforcement Learning of Multi-agent Quadcopter Controlcited by 68
  3. 2021Robot Learning from Randomized Simulations: A Reviewcited by 56
  4. 2023DexPBT: Scaling up Dexterous Manipulation for Hand-Arm Systems with Population Based Trainingcited by 24
  5. 2021Robust High-speed Running for Quadruped Robots via Deep Reinforcement Learningcited by 20
  6. 2023Learning to Fly in Secondscited by 18
  7. 2025See, Point, Fly: A Learning-Free VLM Framework for Universal Unmanned Aerial Navigationcited by 18
  8. 2023DATT: Deep Adaptive Trajectory Tracking for Quadrotor Controlcited by 11
  9. 2025From Screens to Scenes: A Survey of Embodied AI in Healthcarecited by 10
  10. 2024What Matters in Learning A Zero-Shot Sim-to-Real RL Policy for Quadrotor Control? A Comprehensive Studycited by 9
  11. 2023Deep Model Predictive Optimizationcited by 7
  12. 2023Collision Avoidance and Navigation for a Quadrotor Swarm Using End-to-end Deep Reinforcement Learningcited by 6
24 more
  1. 2021Inclined Quadrotor Landing using Deep Reinforcement Learningcited by 5
  2. 2023Optimizing Irrigation Efficiency using Deep Reinforcement Learning in the Fieldcited by 5
  3. 2023QuadSwarm: A Modular Multi-Quadrotor Simulator for Deep Reinforcement Learning with Direct Thrust Controlcited by 5
  4. 2025One Net to Rule Them All: Domain Randomization in Quadcopter Racing Across Different Platformscited by 5
  5. 2021How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control?cited by 4
  6. 2021Robust Deep Reinforcement Learning for Quadcopter Controlcited by 4
  7. 2022Using Simulation Optimization to Improve Zero-shot Policy Transfer of Quadrotorscited by 4
  8. 2022Equivariant Reinforcement Learning for Quadrotor UAVcited by 4
  9. 2023RLtools: A Fast, Portable Deep Reinforcement Learning Library for Continuous Controlcited by 4
  10. 2023HyperPPO: A scalable method for finding small policies for robotic controlcited by 4
  11. 2025Leveling the Playing Field: Carefully Comparing Classical and Learned Controllers for Quadrotor Trajectory Trackingcited by 4
  12. 2025RAPTOR: A Foundation Policy for Quadrotor Controlcited by 4
  13. 2022Inverted Landing in a Small Aerial Robot via Deep Reinforcement Learning for Triggering and Control of Rotational Maneuverscited by 3
  14. 2024Skill Transfer and Discovery for Sim-to-Real Learning: A Representation-Based Viewpointcited by 3
  15. 2025Never too Prim to Swim: An LLM-Enhanced RL-based Adaptive S-Surface Controller for AUVs under Extreme Sea Conditionscited by 3
  16. 2021Reinforcement Learning with Formal Performance Metrics for Quadcopter Attitude Control under Non-nominal Contextscited by 2
  17. 2024Self-organized free-flight arrival for urban air mobilitycited by 2
  18. 2024Leveraging Symmetry to Accelerate Learning of Trajectory Tracking Controllers for Free-Flying Robotic Systemscited by 2
  19. 2022Training Robots to Evaluate Robots: Example-Based Interactive Reward Functions for Policy Learningcited by 1
  20. 2023Sim-Anchored Learning for On-the-Fly Adaptationcited by 0
  21. 2023Curiosity-Driven Reinforcement Learning based Low-Level Flight Controlcited by 0
  22. 2024FPGA-Based Neural Thrust Controller for UAVscited by 0
  23. 2025Learning to Dock: A Simulation-based Study on Closing the Sim2Real Gap in Autonomous Underwater Dockingcited by 0
  24. 2026Embodiment-conditioned Generalist Control for Multirotor Aerial Robotscited by 0