Accurate Tracking of Aggressive Quadrotor Trajectories using Incremental Nonlinear Dynamic Inversion and Differential Flatness
Not on the map. Why?
Abstract (arXiv)
Autonomous unmanned aerial vehicles (UAVs) that can execute aggressive (i.e., high-speed and high-acceleration) maneuvers have attracted significant attention in the past few years. This paper focuses on accurate tracking of aggressive quadcopter trajectories. We propose a novel control law for tracking of position and yaw angle and their derivatives of up to fourth order, specifically, velocity, acceleration, jerk, and snap along with yaw rate and yaw acceleration. Jerk and snap are tracked using feedforward inputs for angular rate and angular acceleration based on the differential flatness of the quadcopter dynamics. Snap tracking requires direct control of body torque, which we achieve using closed-loop motor speed control based on measurements from optical encoders attached to the motors. The controller utilizes incremental nonlinear dynamic inversion (INDI) for robust tracking of linear and angular accelerations despite external disturbances, such as aerodynamic drag forces. Hence, prior modeling of aerodynamic effects is not required. We rigorously analyze the proposed control law through response analysis, and we demonstrate it in experiments. The controller enables a quadcopter UAV to track complex 3D trajectories, reaching speeds up to 12.9 m/s and accelerations up to 2.1g, while keeping the root-mean-square tracking error down to 6.6 cm, in a flight volume that is roughly 18 m by 7 m and 3 m tall. We also demonstrate the robustness of the controller by attaching a drag plate to the UAV in flight tests and by pulling on the UAV with a rope during hover.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Sep 2018.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 3; 2023: 2; 2024: 2; 2025: 3; 2026: 1.
12 papers.
- 2022Neural-Fly Enables Rapid Learning for Agile Flight in Strong Windscited by 80
- 2022Active Learning of Discrete-Time Dynamics for Uncertainty-Aware Model Predictive Controlcited by 13
- 2024SOUS VIDE: Cooking Visual Drone Navigation Policies in a Gaussian Splatting Vacuumcited by 13
- 2023DATT: Deep Adaptive Trajectory Tracking for Quadrotor Controlcited by 11
- 2021Meta-Learning-Based Robust Adaptive Flight Control Under Uncertain Wind Conditionscited by 8
- 2023Constrained Reinforcement Learning using Distributional Representation for Trustworthy Quadrotor UAV Tracking Controlcited by 5
- 2025Leveling the Playing Field: Carefully Comparing Classical and Learned Controllers for Quadrotor Trajectory Trackingcited by 4
- 2022Interpretable Stochastic Model Predictive Control using Distributional Reinforced Estimation for Quadrotor Tracking Systemscited by 1
- 2024Why Change Your Controller When You Can Change Your Planner: Drag-Aware Trajectory Generation for Quadrotor Systemscited by 1
- 2025Decentralized Aerial Manipulation of a Cable-Suspended Load using Multi-Agent Reinforcement Learningcited by 1
- 2025Real-Time Sampling-based Online Planning for Drone Interceptioncited by 0
- 2026Conflict-Predictive Variable Horizons in Multi-Drone Distributed Model Predictive Controlcited by 0
- 2026Conflict-Predictive Variable Horizons in Multi-Drone Distributed Model Predictive Control7 Sep 2026
- 2025Decentralized Aerial Manipulation of a Cable-Suspended Load using Multi-Agent Reinforcement Learning2 Aug 2025
- 2025Leveling the Playing Field: Carefully Comparing Classical and Learned Controllers for Quadrotor Trajectory Tracking21 Jun 2025
- 2025Real-Time Sampling-based Online Planning for Drone Interception20 Feb 2025
- 2024SOUS VIDE: Cooking Visual Drone Navigation Policies in a Gaussian Splatting Vacuum20 Dec 2024
- 2024Why Change Your Controller When You Can Change Your Planner: Drag-Aware Trajectory Generation for Quadrotor Systems10 Jan 2024
- 2023DATT: Deep Adaptive Trajectory Tracking for Quadrotor Control13 Oct 2023
- 2023Constrained Reinforcement Learning using Distributional Representation for Trustworthy Quadrotor UAV Tracking Control22 Feb 2023
- 2022Active Learning of Discrete-Time Dynamics for Uncertainty-Aware Model Predictive Control23 Oct 2022
- 2022Interpretable Stochastic Model Predictive Control using Distributional Reinforced Estimation for Quadrotor Tracking Systems14 May 2022
- 2022Neural-Fly Enables Rapid Learning for Agile Flight in Strong Winds13 May 2022
- 2021Meta-Learning-Based Robust Adaptive Flight Control Under Uncertain Wind Conditions2 Mar 2021