U.S. Patent 12703520, titled “Unmanned aerial vehicles including removable gimbal modules,” was recently awarded to Skydio, Inc. The invention was developed by inventors Alexander David Savello, Christopher Michael Schwab, Yevgeniy Andreyevich Kozlenko, and Patrick Allen Lowe, and it presents a highly modular approach to drone hardware and sensor integration.
This development was named the Patent of the Month for the drones-transportation-tech industry for September 2026. The invention is notably innovative because it introduces an unmanned aerial vehicle chassis configured specifically for a removable gimbal module. By allowing for the repeated connection and disconnection of the gimbal, the design facilitates seamless interchangeability among a plurality of gimbal modules. Instead of replacing an entire aircraft to deploy different optical components, operators can simply swap the camera module to fit their specific operational requirements, which significantly improves fleet versatility and reduces equipment costs in the transportation and logistics sectors.
Practical Applications and U.S. R&D Tax Credit Eligibility
The practical applications of this interchangeable gimbal technology provide a strong foundation for companies seeking the Research and Development (R&D) tax credit in the United States. When businesses integrate these modular concepts into their own operations, such as designing specialized sensor payloads to attach to a modular chassis, developing proprietary firmware to automatically calibrate newly swapped optical components, or testing the aerodynamic stability of the drone when equipped with varying gimbal weights, they are engaging in qualified research activities. Under the IRS four-part test, these iterative engineering and testing processes are conducted to eliminate technical uncertainty and are fundamentally technological in nature. Consequently, businesses investing time and resources into these experimental integrations can claim the R&D tax credit to offset the engineering and development costs of their advanced drone transportation projects.
