Wake Vectoring for Efficient Morphing Flight

Abstract

Morphing aerial robots have the potential to transform autonomous flight, enabling navigation through cluttered environments, perching, and seamless transitions between aerial and terrestrial locomotion. Yet mid-flight reconfiguration presents a critical aerodynamic challenge: tilting propulsors to achieve shape change reduces vertical thrust, undermining stability and control authority. Here, we introduce a passive wake vectoring mechanism that recovers lost thrust during morphing. Integrated into a novel robotic system, Aerially Transforming Morphobot (ATMO), internal deflectors intercept and redirect rotor wake downward, passively steering airflow momentum that would otherwise be wasted. This electronics-free solution achieves up to a 40% recovery of vertical thrust in configurations where no useful thrust would otherwise be produced, substantially extending hover and maneuvering capabilities during transformation. Our findings highlight a new direction for morphing aerial robot design, where passive aerodynamic structures, inspired by thrust vectoring in rockets and aircraft, enable efficient, agile flight without added mechanical complexity.

Figures (6)

• Figure 1: Proposed wake vectoring solution.a Example of a Morphing Aerial Robot, the Aerially Transforming Morphobot (ATMO). This robot is capable of the Morpho-Transition maneuver where the robot transitions from flying to driving in one smooth aerial transformation maneuver. During this maneuver, the rotors are tilted away from the vertical axis resulting in lower thrust available in the vertical direction. reproduced with permission from Mandralis2025-commeng. b Our proposed solution is inspired by the flow manipulation techniques used in aircraft design and rocketry. A passive flow deflector is incorporated behind each wheel-thruster combination. This intercepts and redirects the rotor wake, resulting in extended momentum recovery during transition or in transformed configurations.
• Figure 2: Benchtop Experimental Setup.a Schematic of benchtop test rig with electronic placement, wiring, and dimensions depicted. The thrusters can rotate by servo motors which are controlled from a central microcontroller labeled ($\mu C$). The power supply consists of a 16.8V DC supply that is stepped down to 12V to power the servo motors, and feeds 16.8V to the ESCs which control the rotational speed of two Brushless DC motors (BLDC). A load cell is attached to the top of the test rig and the thrust data is read into a PC using a digital acquisition (DAQ) module. The deflectors are incorporated rigidly onto the main frame. The setup is symmetric to eliminate moment crosstalk interference. b 3D model of the experimental setup. The load cell is depicted, and the propellers are attached to rigid bars that rotate due to a servo motor attached at the pivot point. Everything is mounted onto a rigid frame to eliminate vibrations.
• Figure 3: Thrust Recovery Results for Benchtop Experiment.a One half of the benchtop experiment is depicted with key quantities labeled. $\bm R$ is the force acting on the deflector due to the propeller flow, $T_p$ is the thrust produced by the spinning propeller, and $T$ is the overall level of vertical thrust acting on the propeller-deflector assembly. $\theta$ is the rotation of the deflector from the baseline configuration where the deflector is pointing vertically down, and $\varphi$ is the tilt angle of the propeller thrust axis. b Thrust values from the experimental setup as a function of $\varphi$ for two different deflector angles $\theta\in\{0^\circ,10^\circ\}$ as a ratio of the thrust at $\varphi=0^\circ$. The thrust with no deflectors in place is plotted in black showing close agreement with the theoretical $\cos\varphi$ decay curve. The result of the numerical flow simulations are overlayed with x markers over the $\theta=10^\circ$ and $\theta=20^\circ$ cases, showing reasonable agreement. c Thrust recovery as a ratio of the thrust level at $\varphi=0^\circ$ for two different deflector exit angles.
• Figure 4: Influence of Deflector Exit Angle on Thrust Recovery.a Schematic of the computational domain used for numerical flow simulations. A two-dimensional slice of the three-dimensional domain is depicted. The actuator disk is a cell zone of diameter equal to the propeller diameter $D$ that is tilted at an angle $\varphi$ from the vertical axis. A 2D slice of the deflector and the deflector exit angle $\theta$ is depicted. b Thrust values as a ratio of the thrust at $\varphi=0^\circ$ are plotted for 5 different exit angles $\theta\in \{0^\circ,10^\circ,20^\circ,30^\circ,40^\circ\}$. c Thrust recovery values for the same exit angles. d,e Representative pressure fields for two cases are shown. The streamlines from the 3D velocity field are projected onto the two-dimensional slice.
• Figure 5: Implementation of Wake Vectoring Method on Aerially Transforming Morphobot (ATMO).a Load cell test rig. ATMO is mounted on a robotic arm with a load-cell that measures the vertical force. Tufts have been included on one of the deflectors for some visual feedback of the flow field near the deflector surface. b The deflectors implemented on ATMO. c Thrust values as a ratio of the thrust at $\varphi=0^\circ$ for both deflector designs compared to the $\cos\varphi$ decay curve. d Thrust recovery values for both deflectors. (right) The two deflector design are shown from the frontal perspective. The Deflector 2 design implements insight from benchtop experiments and numerical flow simulations by maximizing the exit angle of the deflector, achieving superior performance.