Organizations: School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, China. · Autonomous Robotics Research Centre, Technology Innovation Institute, P.O.Box: 9639, Masdar City, Abu Dhabi, United Arab Emirates.
Acceleration-commanded guidance laws (e.g., proportional navigation) are attractive for high-level decision making, but their direct deployment on fixed-wing UAVs is challenging because accelerations are not directly actuated and must be realized through attitude and thrust under flight-envelope constraints. This paper presents an acceleration-level outer-loop control framework that converts commanded tangential and normal accelerations into executable body-rate and normalized thrust commands compatible with mainstream autopilots (e.g., PX4/APM). For the normal channel, we derive an engineering mapping from the desired normal acceleration to roll- and pitch-rate commands that regulate the direction and magnitude of the lift vector under small-angle assumptions. For the tangential channel, we introduce an energy-based formulation inspired by total energy control and identify an empirical thrust-energy acceleration relationship directly from flight data, avoiding explicit propulsion modeling or thrust bench calibration. We further discuss priority handling between normal and tangential accelerations under saturation and non-level maneuvers. Extensive real-flight experiments on a VTOL fixed-wing platform demonstrate accurate acceleration tracking and enable practical implementation of proportional navigation using only body-rate and normalized thrust interfaces.
Figures & tables
Fi
Inertial reference frame using the North–East–Down (NED) convention
Fv2
Intermediate reference frame obtained by rotating Fi through yaw and pitch angles
Fb
Body-fixed frame attached to the center of mass of the vehicle
Fv
Velocity frame
x∗,y∗,z∗
Axes of the reference frame F∗
ex∗,ey∗,ez∗
Unit vectors along the positive x -, y -, and z -axes of frame F∗ , respectively
xx∗,xy∗,xz∗,
The component of vector x along the x -, y -, and z -axes of the coordinate frame F∗ , respectively; xx∗=x⋅ex∗
TABLE I: Nomenclature
Fig. 1: SkyFury VTOL fixed-wing Platform.
Parameter
Value
Wingspan
2.50 m
Length
1.26 m
Empty weight
6.58 kg
Battery weight
4.72 kg
Maximum payload
6.92 kg
Max. takeoff weight (MTOW)
13.50 kg
TABLE II: Key parameters of the VTOL SkyFury
Fig. 2: Relationship between Va2 and aTE at Tc=0.7 .
Fig. 3: Relationship between aTE and Tc at Va=20m/s .
Fig. 4: Results of the coupled normal–tangential acceleration response experiment. (a)–(c) Command and measured body-frame accelerations along the x , y , and z axes. The light-blue curves denote raw measured signals, while the dark-blue curves represent moving-average filtered data over a 10-sample window. The black dash-dotted curves show the corresponding responses obtained from Gazebo simulation under the same command sequence. (d) Ground speed and normalized thrust command Tc .
Fig. 5: Results of the proportional navigation flight experiment. (a) Flight trajectory and virtual target point. Miss distance: 0.58 m. (b)–(d) Command and measured body-frame accelerations along the x , y , and z axes. Light-blue curves represent raw measured signals, and dark-blue curves show moving-average filtered data over a 10-sample window.
Aerial robotics studies the design, perception, control, and coordination of flying robots for navigation, inspection, transport, and physical interaction.
Autonomous fixed-wing flight is becoming a key capability in aerial robotics, enabling sensing, mobility, and contingency operations across both small-scale Uncrewed Aircraft Systems and large-scale Advanced Air Mobility. During unpowered operation in fixed-wing platforms, airspeed is regulated solely through potential-kinetic energy exchange, making airspeed dynamics highly sensitive to guidance commands, particularly under wind. This paper presents a viability-based airspeed protection for ground-referenced guidance in steady wind, where airspeed evolution depends explicitly on the commanded flight path angle. Leveraging Nagumo's tangency condition, we derive a closed-form, wind-dependent characterization of admissible guidance commands that guarantees forward invariance of a safe airspeed envelope. These conditions are embedded within an offline quadratic programming framework to certify airspeed-safe maneuver primitives for non-ascending flight at the guidance level. The approach is validated using a high-fidelity unpowered fixed-wing aircraft model on gliding trajectories formed by concatenating certified maneuver primitives, demonstrating strict airspeed boundedness. Future work will address unsteady wind fields and flight experiments.
Huseyin Emre Tekaslan, Ella M. Atkins
Kevin T. Crofton Department of Aerospace and Ocean Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24060, USA
This paper addresses the three-dimensional path-following guidance problem for unmanned aerial vehicles under explicit actuator constraints. Unlike conventional approaches that assume unbounded control inputs or handle saturation heuristically, the proposed method incorporates bounded lateral acceleration directly into the guidance design. A nonlinear guidance framework is developed employing a nested saturation-based control technique. The proposed guidance strategy guarantees bounded control inputs while ensuring exponential convergence of cross-track errors to zero. The formulation is applicable to general smooth paths and is systematically extended from planar to three-dimensional scenarios using a path-tangent coordinate framework. Rigorous stability analysis based on Lyapunov theory establishes convergence and feasibility properties of the closed-loop system. Numerical simulations on representative paths, including straight-line, circular, and sinusoidal paths, demonstrate that the proposed method achieves superior tracking performance, reduced control effort, and robustness against disturbances compared to existing guidance laws. The simplicity of the design and its compatibility with practical actuator limits make it suitable for real-world UAV applications.
Fully actuated omnidirectional UAVs enable independent control of forces and torques along all six degrees of freedom, broadening the operational envelope for agile flight and aerial interaction tasks. However, conventional control allocation methods neglect the asymmetric dynamics of the onboard actuators, which can induce oscillatory motor commands and degrade trajectory tracking during dynamic maneuvers. This work proposes a receding-horizon, actuation-aware allocation strategy that explicitly incorporates asymmetric motor dynamics and exploits the redundancy of over-actuated platforms through nullspace optimization. By forward-simulating the closed-loop system over a prediction horizon, the method anticipates actuator-induced oscillations and suppresses them through smooth redistribution of motor commands, while preserving the desired body wrench exactly. The approach is formulated as a constrained optimal control problem solved online via Constrained iterative LQR. Simulation results on the OmniOcta platform demonstrate that the proposed method significantly reduces motor command oscillations compared to a conventional single-step quadratic programming allocator, yielding improved trajectory tracking in both position and orientation.
Riccardo Pretto, Mahmoud Hamandi, Abdullah Mohamed Ali +3
Tampere University, Finland · New York University Abu Dhabi, Abu Dhabi, UAE