mlsanityData to 14 Oct 2026

OmniDrones: An Efficient and Flexible Platform for Reinforcement Learning in Drone Control

arXiv 2309.12825 ↗First posted 22 Sep 2023cs.RO cs.AI cs.LGcited by 33

Not on the map. Why?

Abstract (arXiv)

In this work, we introduce OmniDrones, an efficient and flexible platform tailored for reinforcement learning in drone control, built on Nvidia's Omniverse Isaac Sim. It employs a bottom-up design approach that allows users to easily design and experiment with various application scenarios on top of GPU-parallelized simulations. It also offers a range of benchmark tasks, presenting challenges ranging from single-drone hovering to over-actuated system tracking. In summary, we propose an open-sourced drone simulation platform, equipped with an extensive suite of tools for drone learning. It includes 4 drone models, 5 sensor modalities, 4 control modes, over 10 benchmark tasks, and a selection of widely used RL baselines. To showcase the capabilities of OmniDrones and to support future research, we also provide preliminary results on these benchmark tasks. We hope this platform will encourage further studies on applying RL to practical drone systems.

Key facts. Cited by 33 papers in the map (data through 14 Oct 2026). Builds on 33 of its 47 references that are in the map. First posted on arXiv 22 Sep 2023.

Builds on

33 of 47 references.

References · 33

  1. 2017Proximal Policy Optimization Algorithmscited by 15,215
  2. 2018Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actorcited by 4,885
  3. 2018Addressing Function Approximation Error in Actor-Critic Methodscited by 2,417
  4. 2014Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modelingcited by 2,367
  5. 2017Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environmentscited by 1,558
  6. 2019Dota 2 with Large Scale Deep Reinforcement Learningcited by 1,103
  7. 2021Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learningcited by 998
  8. 2018DeepMind Control Suitecited by 956
  9. 2021The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Gamescited by 942
  10. 2015End-to-End Training of Deep Visuomotor Policiescited by 875
  11. 2019RLBench: The Robot Learning Benchmark & Learning Environmentcited by 689
  12. 2017AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehiclescited by 523
21 more
  1. 2021Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learningcited by 512
  2. 2021RMA: Rapid Motor Adaptation for Legged Robotscited by 508
  3. 2020Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learningcited by 485
  4. 2023Orbit: A Unified Simulation Framework for Interactive Robot Learning Environmentscited by 295
  5. 2021Trust Region Policy Optimisation in Multi-Agent Reinforcement Learningcited by 186
  6. 2022Towards Human-Level Bimanual Dexterous Manipulation with Reinforcement Learningcited by 119
  7. 2017Control of a Quadrotor with Reinforcement Learningcited by 92
  8. 2020Flightmare: A Flexible Quadrotor Simulatorcited by 84
  9. 2021Learning to Fly -- a Gym Environment with PyBullet Physics for Reinforcement Learning of Multi-agent Quadcopter Controlcited by 77
  10. 2021Autonomous Drone Racing with Deep Reinforcement Learningcited by 60
  11. 2023TorchRL: A data-driven decision-making library for PyTorchcited by 60
  12. 2018Reinforcement Learning for UAV Attitude Controlcited by 48
  13. 2022A Benchmark Comparison of Learned Control Policies for Agile Quadrotor Flightcited by 47
  14. 2019Low Level Control of a Quadrotor with Deep Model-Based Reinforcement Learningcited by 44
  15. 2015Learning Deep Control Policies for Autonomous Aerial Vehicles with MPC-Guided Policy Searchcited by 42
  16. 2018Deep Drone Racing: Learning Agile Flight in Dynamic Environmentscited by 34
  17. 2020Model-Based Meta-Reinforcement Learning for Flight with Suspended Payloadscited by 30
  18. 2019FlightGoggles: A Modular Framework for Photorealistic Camera, Exteroceptive Sensor, and Dynamics Simulationcited by 22
  19. 2022Learning a Single Near-hover Position Controller for Vastly Different Quadcopterscited by 21
  20. 2023Aerial Gym -- Isaac Gym Simulator for Aerial Robotscited by 11
  21. 2022Downwash-aware Control Allocation for Over-actuated UAV Platformscited by 3

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 2; 2024: 9; 2025: 11; 2026: 11.

33 papers.

Sort:

By area:

  1. 2024NavRL: Learning Safe Flight in Dynamic Environmentscited by 26
  2. 2024SOUS VIDE: Cooking Visual Drone Navigation Policies in a Gaussian Splatting Vacuumcited by 16
  3. 2024ACEGEN: Reinforcement learning of generative chemical agents for drug discoverycited by 14
  4. 2024What Matters in Learning A Zero-Shot Sim-to-Real RL Policy for Quadrotor Control? A Comprehensive Studycited by 11
  5. 2025BEDI: A Comprehensive Benchmark for Evaluating Embodied Agents on UAVscited by 10
  6. 2025MarineGym: A High-Performance Reinforcement Learning Platform for Underwater Roboticscited by 8
  7. 2024VisFly: An Efficient and Versatile Simulator for Training Vision-based Flightcited by 7
  8. 2026CARLA-Air: Fly Drones Inside a CARLA World -- A Unified Infrastructure for Air-Ground Embodied Intelligencecited by 5
  9. 2024Online Planning for Multi-UAV Pursuit-Evasion in Unknown Environments Using Deep Reinforcement Learningcited by 4
  10. 2025VolleyBots: A Testbed for Multi-Drone Volleyball Game Combining Motion Control and Strategic Playcited by 4
  11. 2025Decentralized Aerial Manipulation of a Cable-Suspended Load using Multi-Agent Reinforcement Learningcited by 4
  12. 2025RoVerFly: Robust and Versatile Implicit Hybrid Control of Quadrotor-Payload Systemscited by 4
21 more
  1. 2025Learned Controllers for Agile Quadrotors in Pursuit-Evasion Gamescited by 3
  2. 2025DiffAero: A GPU-Accelerated Differentiable Simulation Framework for Efficient Quadrotor Policy Learningcited by 3
  3. 2026AirDreamer: Generalist Drone Navigation with World Modelscited by 3
  4. 2024Current applications and potential future directions of reinforcement learning-based Digital Twins in agriculturecited by 2
  5. 2024Flying Quadrotors in Tight Formations using Learning-based Model Predictive Controlcited by 2
  6. 2024Neural Internal Model Control: Learning a Robust Control Policy via Predictive Error Feedbackcited by 2
  7. 2023A Dual Curriculum Learning Framework for Multi-UAV Pursuit-Evasion in Diverse Environmentscited by 1
  8. 2025Curriculum-based Sample Efficient Reinforcement Learning for Robust Stabilization of a Quadrotorcited by 1
  9. 2025Towards Task-Oriented Flying: Framework, Infrastructure, and Principlescited by 1
  10. 2025MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objectscited by 1
  11. 2025JuggleRL: Mastering Ball Juggling with a Quadrotor via Deep Reinforcement Learningcited by 1
  12. 2026RobotWorld: Benchmarking Multimodal Agents for Robot Use Across Diverse Tasks and Embodimentscited by 1
  13. 2023MASP: Scalable GNN-based Planning for Multi-Agent Navigationcited by 0
  14. 2026Communication-Free Collective Navigation for a Swarm of UAVs via LiDAR-Based Deep Reinforcement Learningcited by 0
  15. 2026Conformal Reachability for Safe Control in Unknown Environmentscited by 0
  16. 2026Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learningcited by 0
  17. 2026PerchRL: Vision-Based Agile Perching on Inclined Platforms under Rapid and Irregular Motioncited by 0
  18. 2026MuJoCo-Drones-Gym: A GPU-Accelerated Multi-Drone Simulator for Control and Reinforcement Learningcited by 0
  19. 2026Anticipatory Risk-Guided Reinforcement Learning for Safe Flight Through Dynamic Cluttercited by 0
  20. 2026AgilePE: Autonomous UAV Pursuit-Evasion via Self-Play Reinforcement Learningcited by 0
  21. 2026GzDRL: Reproducible and Scalable Deep Reinforcement Learning with Gazebocited by 0