Single Drone
Single drone research focuses on enhancing drone capabilities for diverse applications, primarily addressing limitations in battery life, operational range, and data processing. Current research emphasizes improving autonomy through deep reinforcement learning (DRL) and advanced control algorithms like PID controllers, often coupled with robust sensor fusion techniques (e.g., visual, infrared, and RF) and novel navigation strategies for GPS-denied environments. These advancements are significant for various fields, including environmental monitoring, search and rescue, infrastructure inspection, and delivery services, by enabling more efficient, reliable, and versatile drone operations.
Papers
TumblerBots: Tumbling Robotic sensors for Minimally-invasive Benthic Monitoring
L. Romanello, A. Teboul, F. Wiesemuller, P. H. Nguyen, M. Kovac, S. F. Armanini
Exploring the Potential of Multi-modal Sensing Framework for Forest Ecology
Luca Romanello, Tian Lan, Mirko Kovac, Sophie F. Armanini, Basaran Bahadir Kocer
SPIBOT: A Drone-Tethered Mobile Gripper for Robust Aerial Object Retrieval in Dynamic Environments
Gyuree Kang, Ozan Güneş, Seungwook Lee, Maulana Bisyir Azhari, David Hyunchul Shim
Distance-based Multiple Non-cooperative Ground Target Encirclement for Complex Environments
Fen Liu, Shenghai Yuan, Kun Cao, Wei Meng, Lihua Xie