The technology, named T-STAR, enables swarms of drones to communicate and adapt in real time. Each drone can instantly alter its path to avoid collisions while maintaining formation, ensuring the group continues toward its target with minimal disruption.
Traditional systems often require drones to slow down drastically in cluttered or unpredictable environments. By contrast, T-STAR maintains high performance even in obstacle-rich settings, completing missions faster and with smoother trajectories.
"T-STAR allows autonomous aerial vehicles to operate as a truly intelligent swarm, combining speed, safety, and coordination in ways that were previously impossible," said lead author Dr Junyan Hu of Durham University. "This opens up new possibilities for using cooperative robotic swarms in complex scenarios, where every second counts."
Applications range from emergency response and wildfire monitoring to environmental exploration, agriculture, and parcel delivery. In disaster zones, coordinated swarms could deliver supplies or locate survivors far more efficiently than current approaches.
The system's design balances autonomy and teamwork. Each drone retains independence yet functions as part of a dynamic network, similar to birds in flight. This duality grants both resilience and adaptability, allowing swarms to navigate sudden challenges.
Initial laboratory and simulation tests confirmed T-STAR's advantages, and researchers are preparing to expand trials into outdoor environments, paving the way toward practical deployment at scale.
Research Report:T-STAR: Time-Optimal Swarm Trajectory Planning for Quadrotor Unmanned Aerial Vehicles
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Durham University
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