System for continuously controlling quadrotor drone behavior using Signal Temporal Logic (STL) as the mission specification language

Autonomous drones are increasingly being used for advanced applications such as package delivery, surveillance, and infrastructure monitoring. However, the requirement of complex instructions for spatial, temporal, and reactive navigation makes controlling drone systems challenging. Most existing encoding systems are simplified and limited, and do not consider timing constraints, scalability, or real-world behaviors.

Dr. Mangharam and colleagues at the University of Pennsylvania have designed a new algorithm to control quadrotor drone behavior continuously using Signal Temporal Logic (STL). The method enables the consideration of explicit timing requirements and use of the full expressiveness of STL to optimize a smooth trajectory for drone movement. The system offers continuous-time STL satisfaction, feasible movement trajectories, and real-time drone control with scalability, providing a control framework for mission planning and execution for fleets of quadrotors.

• Avoids oversimplifying abstractions while using off-the-shelf sensors and limited computation
• Handles complex spatial, temporal and reactive requirements for drone missions
• Scales well for problems involving up to 16 drones
• Maximizes robustness in generating trajectories for quadrotors in continuous-time