TY - GEN
T1 - Antenna Pattern Aware UAV Trajectory Planning Using Artificial Potential Field
AU - Sulieman, M. Hani
AU - Gursoy, M. Cenk
AU - Kong, Fanxin
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Unmanned aerial vehicles (UAVs) have numerous applications in various scenarios and disciplines including wireless communications and Internet of Things (IoT). This paper studies the trajectory design and collision avoidance in both single-UAV and multiple-UAV settings. During a mission, UAVs communicate with the ground base stations (GBS). In this work, it is assumed that UAVs are equipped with antennas with different radiation patterns. These antenna patterns impact the trajectory design of the UAVs. To achieve efficient performance in UAV trajectory planning, we implement an enhanced-artificial potential field (enhanced-APF) algorithm. The implemented algorithm leads to UAV trajectory designs with collision avoidance, and enables us to identify the overall impact of the 3D antenna patterns on the UAV trajectory. The experimental results demonstrate the effectiveness and the performance of the algorithm, resulting in a smoother trajectory path for UAVs.
AB - Unmanned aerial vehicles (UAVs) have numerous applications in various scenarios and disciplines including wireless communications and Internet of Things (IoT). This paper studies the trajectory design and collision avoidance in both single-UAV and multiple-UAV settings. During a mission, UAVs communicate with the ground base stations (GBS). In this work, it is assumed that UAVs are equipped with antennas with different radiation patterns. These antenna patterns impact the trajectory design of the UAVs. To achieve efficient performance in UAV trajectory planning, we implement an enhanced-artificial potential field (enhanced-APF) algorithm. The implemented algorithm leads to UAV trajectory designs with collision avoidance, and enables us to identify the overall impact of the 3D antenna patterns on the UAV trajectory. The experimental results demonstrate the effectiveness and the performance of the algorithm, resulting in a smoother trajectory path for UAVs.
KW - antenna patterns
KW - artificial potential field
KW - collision avoidance
KW - ground base stations
KW - unmanned aerial vehicles
UR - http://www.scopus.com/inward/record.url?scp=85122817339&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85122817339&partnerID=8YFLogxK
U2 - 10.1109/DASC52595.2021.9594394
DO - 10.1109/DASC52595.2021.9594394
M3 - Conference contribution
AN - SCOPUS:85122817339
T3 - AIAA/IEEE Digital Avionics Systems Conference - Proceedings
BT - 40th Digital Avionics Systems Conference, DASC 2021 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 40th IEEE/AIAA Digital Avionics Systems Conference, DASC 2021
Y2 - 3 October 2021 through 7 October 2021
ER -