The MIT researchers have developed a planning algorithm for tailsitter aircraft that uses differential flatness, a mathematical function that reduces the number of calculations needed, making trajectory planning for tailsitters much more efficient and enabling real-time planning and execution of complex maneuvers. In addition to trajectory planning, the team also developed control algorithms that enable the tailsitter to follow the planned trajectory with precision, even in the face of external disturbances like wind gusts. The control algorithm uses feedback from the vehicle's sensors to adjust the wings and rotors, enabling the aircraft to smoothly transition between different flight modes and execute acrobatic maneuvers. Overall, the MIT researchers' approach to trajectory planning and control is a major step forward for tailsitter aircraft and could enable these versatile vehicles to perform complex search-and-rescue missions and other tasks that are currently difficult or impossible for quadcopter drones to execute.