A system from the Massachusetts Institute of Technology's Computer Science and Artificial Intelligence Laboratory (CSAIL) allows users to design, simulate ,and build their own custom drone.

Users can change the size, shape and structure of the drone based on the specific needs they have for payload, cost, flight time, battery usage, and other factors.

A four-rotor "bunnycopter" features propellers at different heights. Credit: Jason Dorfman/MIT CSAILTo demonstrate, researchers created a range of unusual-looking drones, including a five-rotor "pentacopter" and a rabbit-shaped "bunnycopter" with propellers of different sizes and rotors of different heights.

The interface lets users design drones with different propellers, rotors, and rods. It also provides guarantees that the drones it fabricates can take off, hover and land.

Today's commercial drones generally come in a relatively small range of options, typically with an even number of rotors and upward-facing propellers. But many emerging use cases exist for other kinds of drones. For example, having an odd number of rotors might create a clearer view for a drone's camera, or allow the drone to carry objects with unusual shapes.

Designing these drones, however, often requires expertise in multiple disciplines, including control systems, fabrication, and electronics.

The CSAIL group says its system makes the process easier. Users design drones by choosing from a database of parts and specifying their needs for things like payload, cost, and battery usage. The system computes the sizes of design elements like rod lengths and motor angles, and looks at metrics such as torque and thrust to determine whether the design will fly. It also uses an LQR controller that takes information about a drone's characteristics and surroundings to optimize its flight plan.

One of the project's core challenges stemmed from the fact that a drone's shape and structure (its geometry) is usually tied to how it has been programmed to move (its control). To overcome this, researchers used what's called an "alternating direction method," which means they reduced the number of variables by fixing some of them and optimizing the rest. This allowed the team to decouple the variables of geometry and control in a way that optimizes the drone's performance.

The researchers envision future versions of the system that could proactively give design suggestions, like recommending where a rotor should go to accommodate a desired payload.