To further validate the platform's practical feasibility experimentally, and assess its performance, the hybrid vehicle prototype was subjected to two tests. The first experiment demonstrates the concept's capabilities as an aerial vehicle. The prototype was required to start from rest, take off, and then track some desired path, maintaining a fixed heading orientation. Specifically, the path used forms an inclined eight shape in 3D space. The second test was designed to demonstrate the concept's capabilities as a UAV and a ground vehicle. On it, the prototype performs an emulated search-and-rescue scenario.

The PX4 open-source flight stack of a Pixracer, a flight controller board commonly used for small racing quadrotors, was modified to incorporate the control strategy and inverse kinematics described in the previous section. The original attitude/rate controllers and mixer were adequately modified, while the middleware and other essential parts of the flight stack were kept, e.g., position controller, land/takeoff detector,  real-time task scheduling, and drivers for embedded sensors. The controller's output commands were mapped to the external actuators, i.e., Dynamixel servo motors, by creating an interface to the flight controller using the MAVLink messaging protocol and an OpenCM/Arduino board. The two 2050Kv brushless motors with 7-inch propellers were controlled directly by the flight controller and 4-in-1 ESC. Furthermore, MATLAB/Simulink running on an offboard PC was employed for handling telemetry, parsing and creating MAVLink messages, and transmitting position and orientation data as UDP packets to the flight controller. Pose measurements were obtained using a Vicon motion capture system.

The desired orientation is set to a fixed value of 90 degrees. That orientation was precisely maintained with 1.3 degrees RMS error. Overall, the results are promising and validate the vehicle's ability to track complex 3D paths with satisfactory performance. However, such faults observed in the performance can not be overlooked. Some possibilities could explain the undesired behaviours the system displayed. The vanes' model between counter-rotating coaxial rotors is unknown, and the authors believe that once a model is obtained, control could be improved considerably. Furthermore, a design iteration that favors better rigidity, employing higher-end materials such as carbon fiber instead of PLA for some parts of the design, would reduce low-frequency vibrations and improve sensor readings. The considerable weight present in the Core link can also influence performance by transferring reaction torques due to its movement, disturbing the system. Such an effect could be reduced by increasing the distance between the CG and the thrust's application point with design changes. This would increase the attitude control authority, minimizing the impact of disturbances. Nevertheless, the prototype proved to be consistent in its flight performance and capable of tracking many other trajectories shapes, which are not presented here.

Finally, to illustrate the Omnirotor platform's use as a hybrid vehicle, the concept was tested on a potential search-and-rescue environment. In the first part of this scenario, the vehicle transverses a track on the ground, starting from rest and crossing below a narrow, near-the-floor passage. This part of the experiment is performed with teleoperation, where a pilot controls the vehicle driving on the ground. The inputs from the pilot to the system are sent with a regular radio controller. To generate enough effort to move on the ground, the pilot commands low throttle values but large values of pitch and row. In this mode, the same control mapping and mixer used for flying are employed.

In the second part of the scenario, while traversing the track through the soil, the vehicle is faced with an obstacle it supposedly can not cross as a ground vehicle. The Omnirotor then changes mode switching to work as an aerial vehicle, takeoff, and fly over the obstacle, landing on the other side of it to continue the search. This part of the experiment works in the same way as the path tracking experiment presented in the previous subsection. Controlled offboard by a computer, the vehicle takeoff, fly, and land autonomously with position feedback from the motion capture system. With the present design, flight autonomy is of about 4 to 5 minutes, which is considered low for a coaxial UAV. However, such reduced flight time partially results from the added weight of the smart Dynamixel actuators and their accompanying control boards. Besides, as stressed by the search-and-rescue experiment, the vehicle's hybrid operation has the potential to extend autonomy considerably, multiplying it by up to 4 times, considering it can drive on the ground using about 25% of the throttle required to hover.