Planning algorithm enables high-performance flight
MIT researchers have developed innovative algorithms for trajectory planning and control of tailsitter aircraft, a type of fixed-wing aircraft that can take off and land vertically. Tailsitters are known for their versatility, as they can hover like a helicopter and fly over large areas like an airplane, making them ideal for tasks such as search and rescue or parcel delivery. The new algorithms allow tailsitters to perform complex maneuvers, including sideways and upside-down flight, and can plan these maneuvers in real-time.
The researchers used a novel approach called “ensemble boosting” to develop their algorithms, which exploit the full potential of tailsitter aircraft. Unlike other methods that use simplified models or multiple models for different flight modes, ensemble boosting allows the use of a single model to cover the entire flight envelope and simulate a wide range of flight conditions.
Ensemble boosting employs a global dynamics model and leverages a technical property known as differential flatness to efficiently plan trajectories and check their feasibility. This approach enables rapid real-time trajectory planning, even for complex and aggressive maneuvers.
The researchers demonstrated their algorithms by having tailsitters perform challenging maneuvers, such as loops, rolls, and synchronized acrobatic movements. These algorithms could have applications in dynamic environments, such as autonomous search and rescue operations or other scenarios that require agile and precise flight.
The next step for the researchers is to extend their algorithm for outdoor flight, where environmental conditions like wind could impact the aircraft’s dynamics. The study was supported by the U.S. Army Research Office.
