Disturbance-Aware Flight for Aerial Robots in Narrow Space
2026-07-20 • Robotics
Robotics
AI summaryⓘ
The authors developed a system to help small drones fly safely through tight, windy spaces. Their method measures the wind and forces acting on the drone in real time and uses this information to slow down or speed up the drone as needed. They also designed a special controller that helps the drone stay on its planned path despite these disturbances. Tests showed their drone could navigate very narrow tunnels better and more efficiently than human pilots. This approach improves drone flight in challenging, confined environments by combining planning and control with real-time disturbance awareness.
quadrotoraerodynamic disturbancesmotion planningnonlinear model predictive controldual-loop observertrajectory trackingdisturbance estimationnarrow space flightmotor dynamicsadaptive speed control
Authors
Lei Qiang, Tianyu He, Chenyang Sun, Xurui Liu, Miao Wang, Xiaobin Zhou
Abstract
Autonomous flight of aerial robots in narrow space remains challenging due to strong aerodynamic disturbances and limited flying space. Existing approaches mainly address aerodynamic disturbances at the control level, while motion planning typically relies on geometric constraints and fixed speed limits, leading to conservative or unsafe behaviors in confined environments. This paper presents a disturbance-aware planning and control framework (DAPCF) that integrates online disturbance estimation into the planning-control loop for quadrotor flight in narrow space. First, the dual-loop observers estimate 6-degree-of-freedom disturbance forces and torques in real time based on odometry and motor speed measurements. Then, a disturbance risk function is introduced that adaptively modulates the reference speed of the planner based on disturbance estimation, reducing velocity when disturbances exceed a threshold and restoring it under low-disturbance conditions. Finally, a motor-dynamics-based nonlinear model predictive controller (MDNMPC) with disturbance compensation is designed to ensure robust trajectory tracking under perturbed conditions. Experiments demonstrate that a quadrotor with a diagonal length of 0.39~m can traverse straight, sloped, and curved tunnels as narrow as 0.6~m, outperforming human pilots in both success rate and flight efficiency.