TY - GEN
T1 - Autonomous drone coordination in RF-denied environments through leader-follower systems and computer vision
AU - Kuantama, Endrowednes
AU - James, Alice
AU - Seth, Avishkar
PY - 2024
Y1 - 2024
N2 - Drone swarm technology often employs a leader-follower strategy, where a single drone assumes the role of the leader and directs multiple follower drones. The leader and followers communicate through a designated protocol for seamless data exchange and coordination. This paper addresses scenarios where traditional radio frequency (RF) communication is disrupted or denied, focusing on enhancing the robustness and reliability of drone operations for follower drones. The leader drone can use communication-resistant technologies and advanced computer vision algorithms to guide the follower drones. Additionally, the leader drone features a tail LED light with a directional arrow symbol and three colour variants of blue, yellow and pink for speed display with 0.89,0.98 and 0.96 accuracy rates, respectively. In this proposed design, follower drones maintain a consistent distance, altitude, and angle relative to the leader drone, with the machine learning algorithm utilizing region-based segmentation for practical guidance. Experimental results demonstrate that the system achieves an impressive response time of 10 ms per frame, with an 18 m detection range and less than 1% error for altitude adjustments in low-light conditions. Notably, the follower drones consistently maintain a 9 5% reliability in following the leader with the specified distance and altitude.
AB - Drone swarm technology often employs a leader-follower strategy, where a single drone assumes the role of the leader and directs multiple follower drones. The leader and followers communicate through a designated protocol for seamless data exchange and coordination. This paper addresses scenarios where traditional radio frequency (RF) communication is disrupted or denied, focusing on enhancing the robustness and reliability of drone operations for follower drones. The leader drone can use communication-resistant technologies and advanced computer vision algorithms to guide the follower drones. Additionally, the leader drone features a tail LED light with a directional arrow symbol and three colour variants of blue, yellow and pink for speed display with 0.89,0.98 and 0.96 accuracy rates, respectively. In this proposed design, follower drones maintain a consistent distance, altitude, and angle relative to the leader drone, with the machine learning algorithm utilizing region-based segmentation for practical guidance. Experimental results demonstrate that the system achieves an impressive response time of 10 ms per frame, with an 18 m detection range and less than 1% error for altitude adjustments in low-light conditions. Notably, the follower drones consistently maintain a 9 5% reliability in following the leader with the specified distance and altitude.
UR - http://www.scopus.com/inward/record.url?scp=85208020629&partnerID=8YFLogxK
U2 - 10.1109/ICARM62033.2024.10715791
DO - 10.1109/ICARM62033.2024.10715791
M3 - Conference proceeding contribution
AN - SCOPUS:85208020629
SN - 9798350385731
SP - 741
EP - 746
BT - 2024 9th IEEE International Conference on Advanced Robotics and Mechatronics
PB - Institute of Electrical and Electronics Engineers (IEEE)
CY - Piscataway, NJ
T2 - 9th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2024
Y2 - 8 July 2024 through 10 July 2024
ER -