mlsanityData to 7 Oct 2026

DATT: Deep Adaptive Trajectory Tracking for Quadrotor Control

arXiv 2310.09053 ↗First posted 13 Oct 2023cs.RO cs.AI cs.SYcited by 11

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Abstract (arXiv)

Precise arbitrary trajectory tracking for quadrotors is challenging due to unknown nonlinear dynamics, trajectory infeasibility, and actuation limits. To tackle these challenges, we present Deep Adaptive Trajectory Tracking (DATT), a learning-based approach that can precisely track arbitrary, potentially infeasible trajectories in the presence of large disturbances in the real world. DATT builds on a novel feedforward-feedback-adaptive control structure trained in simulation using reinforcement learning. When deployed on real hardware, DATT is augmented with a disturbance estimator using L1 adaptive control in closed-loop, without any fine-tuning. DATT significantly outperforms competitive adaptive nonlinear and model predictive controllers for both feasible smooth and infeasible trajectories in unsteady wind fields, including challenging scenarios where baselines completely fail. Moreover, DATT can efficiently run online with an inference time less than 3.2 ms, less than 1/4 of the adaptive nonlinear model predictive control baseline

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 22 of its 37 references that are in the map. First posted on arXiv 13 Oct 2023.

Builds on

22 of 37 references.

References · 22

  1. 2017Proximal Policy Optimization Algorithmscited by 14,441
  2. 2021RMA: Rapid Motor Adaptation for Legged Robotscited by 430
  3. 2018Neural Lander: Stable Drone Landing Control using Learned Dynamicscited by 82
  4. 2022Neural-Fly Enables Rapid Learning for Agile Flight in Strong Windscited by 80
  5. 2017Control of a Quadrotor with Reinforcement Learningcited by 75
  6. 2020Deep Drone Acrobaticscited by 66
  7. 2019Sim-to-(Multi)-Real: Transfer of Low-Level Robust Control Policies to Multiple Quadrotorscited by 36
  8. 2021Data-Driven MPC for Quadrotorscited by 32
  9. 2022A Benchmark Comparison of Learned Control Policies for Agile Quadrotor Flightcited by 32
  10. 2020The Power of Predictions in Online Controlcited by 31
  11. 2017Differential Flatness of Quadrotor Dynamics Subject to Rotor Drag for Accurate Tracking of High-Speed Trajectoriescited by 28
  12. 2020Neural-Swarm2: Planning and Control of Heterogeneous Multirotor Swarms using Learned Interactionscited by 19
10 more
  1. 2021A Comparative Study of Nonlinear MPC and Differential-Flatness-Based Control for Quadrotor Agile Flightcited by 19
  2. 2021Performance, Precision, and Payloads: Adaptive Nonlinear MPC for Quadrotorscited by 18
  3. 2022Learning a Single Near-hover Position Controller for Vastly Different Quadcopterscited by 16
  4. 2020L1-Adaptive MPPI Architecture for Robust and Agile Control of Multirotorscited by 14
  5. 2018Accurate Tracking of Aggressive Quadrotor Trajectories using Incremental Nonlinear Dynamic Inversion and Differential Flatnesscited by 12
  6. 2020Aggressive Perception-Aware Navigation using Deep Optical Flow Dynamics and PixelMPCcited by 6
  7. 2019Inverting Learned Dynamics Models for Aggressive Multirotor Controlcited by 1
  8. 2021Feedback Linearization for Quadrotors with a Learned Acceleration Error Modelcited by 1
  9. 2021Non-Parametric Neuro-Adaptive Coordination of Multi-Agent Systemscited by 1
  10. 2023L1Quad: L1 Adaptive Augmentation of Geometric Control for Agile Quadrotors with Performance Guaranteescited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 5; 2025: 4; 2026: 2.

11 papers.

  1. 2025ASAP: Aligning Simulation and Real-World Physics for Learning Agile Humanoid Whole-Body Skillscited by 104
  2. 2024What Matters in Learning A Zero-Shot Sim-to-Real RL Policy for Quadrotor Control? A Comprehensive Studycited by 9
  3. 2024DR-MPC: Deep Residual Model Predictive Control for Real-world Social Navigationcited by 7
  4. 2025Leveling the Playing Field: Carefully Comparing Classical and Learned Controllers for Quadrotor Trajectory Trackingcited by 4
  5. 2025RoVerFly: Robust and Versatile Implicit Hybrid Control of Quadrotor-Payload Systemscited by 4
  6. 2024CoVO-MPC: Theoretical Analysis of Sampling-based MPC and Optimal Covariance Designcited by 3
  7. 2024Leveraging Symmetry to Accelerate Learning of Trajectory Tracking Controllers for Free-Flying Robotic Systemscited by 2
  8. 2024Neural Internal Model Control: Learning a Robust Control Policy via Predictive Error Feedbackcited by 2
  9. 2026Wind-Aware Reinforcement Learning Control of a Small Quadrotor Using Learned Onboard Wind Estimation in Simulated Atmospheric Turbulencecited by 1
  10. 2025AD-NODE: Adaptive Dynamics Learning with Neural ODEs for Mobile Robots Controlcited by 0
  11. 2026Adapting Generalist Vehicle Models for High-Speed MPC Across Terrainscited by 0