Toward collision-free trajectory for autonomous and pilot-controlled unmanned aerial vehicles
Kaya Kuru, John Michael Pinder, Benjamin Jon Watkinson, Darren Ansell,, Keith Vinning, Lee Moore, Chris Gilbert, Aadithya Sujit, and David Jones

TL;DR
This paper introduces the Drone Aware Collision Management (DACM) system, which uses electronic conspicuity data to enable UAVs to perform time-optimal collision avoidance maneuvers in complex, dynamic airspace environments.
Contribution
The study develops and validates a novel reactive collision management methodology that effectively utilizes electronic conspicuity information for UAV collision avoidance without complex sensors or training.
Findings
DACM successfully avoids mid-air collisions in simulations and real-world tests.
The methodology limits trajectory deviation during collision avoidance maneuvers.
DACM operates effectively in highly dynamic aerospace environments.
Abstract
For drones, as safety-critical systems, there is an increasing need for onboard detect & avoid (DAA) technology i) to see, sense or detect conflicting traffic or imminent non-cooperative threats due to their high mobility with multiple degrees of freedom and the complexity of deployed unstructured environments, and subsequently ii) to take the appropriate actions to avoid collisions depending upon the level of autonomy. The safe and efficient integration of UAV traffic management (UTM) systems with air traffic management (ATM) systems, using intelligent autonomous approaches, is an emerging requirement where the number of diverse UAV applications is increasing on a large scale in dense air traffic environments for completing swarms of multiple complex missions flexibly and simultaneously. Significant progress over the past few years has been made in detecting UAVs present in aerospace,…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
MethodsAttentive Walk-Aggregating Graph Neural Network
