Kim et al.'s New Quadcopter Algorithm Enables Robust 3D Trajectory Tracking

A new paper from Kim, Pyrkin, and Borisov presents a complete motion model and robust control algorithm for quadcopters following smooth spatial trajectories. The key innovation is that the controller relies only on measurements of linear coordinates (position) and yaw angle — not full state information such as velocity or orientation angles. By introducing additional integrators into the control loop, the algorithm dramatically simplifies the tuning process for engineers, making it more accessible for real-world deployment. The control law is synthesized using a geometric approach with a rigorous stability proof.

The algorithm's practical value is enhanced by a realizable output-feedback version that incorporates an extended state observer. This observer estimates unmeasured disturbances (e.g., wind gusts) and missing state variables, allowing the quadcopter to maintain precise trajectory tracking even under incomplete sensor data. The work directly addresses a common challenge in drone operations: maintaining coordinated motion in three-dimensional space despite real-world uncertainties. The simplified tuning and reduced sensor requirements could lower the barrier for advanced autonomous flight in applications like delivery drones, aerial inspection, and surveillance.