Optimizing Communication and Computation for Multi-UAV Information Gathering Applications
Department of Aeronautics, Imperial College London（帝国理工学院伦敦校区航空系）；Department of Electronics and Communications Engineering, Indraprastha Institute of Information Technology（印度拉普拉兹信息技术学院电子与通信工程系）；Department of Electrical & Electronic Engineering and the Department of Aeronautics, Imperial College London（帝国理工学院伦敦校区电子与电气工程系及航空系）；Department of Electrical and Computer Engineering, University of Porto（葡萄牙波尔图大学电气与计算机工程系）
Mason Thammawichai, Sujit P. Baliyarasimhuni, Eric C. Kerrigan, João B. Sousa
发表信息：
IEEE Transactions on Aerospace and Electronic Systems ( Volume: 54, Issue: 2, April 2018)
Mobile agent networks, such as multi-UAV systems, are constrained by limited resources. In particular, limited energy affects system performance directly, such as system lifetime. It has been demonstrated in the wireless sensor network literature that the communication energy consumption dominates the computational and the sensing energy consumption. Hence, the lifetime of the multi-UAV systems can be extended significantly by optimizing the amount of communication data, at the expense of increasing computational cost. In this work, we aim at attaining an optimal trade-off between the communication and the computational energy. Specifically, we propose a mixed-integer optimization formulation for a multi-hop hierarchical clustering-based self-organizing UAV network incorporating data aggregation, to obtain an energy-efficient information routing scheme. The proposed framework is tested on two applications, namely target tracking and area mapping. Based on simulation results, our method can significantly save energy compared to a baseline strategy, where there is no data aggregation and clustering scheme.
Optimizing Search and Rescue UAV Connectivity in Challenging Terrain through Multi Q-Learning
School of Electronic and Electrical Engineering, University of Leeds（利兹大学电子与电气工程学院）；College of Electronics Engineering, Ninevah University（尼尼微大学电子工程学院）
Optimizing Indoor Farm Monitoring Efficiency Using UAV: Yield Estimation in a GNSS-Denied Cherry Tomato Greenhouse
Department of Mechanical Engineering, Ulsan National Institute of Science and Technology (UNIST)（机械工程系，乌山国立科学技术研究院）；Agricultural Robotics and Artificial Intelligence, Metafarmers（农业机器人与人工智能，Metafarmers）
Learning Transferable UAV for Forest Visual Perception
Beijing National Research Center for Information Science and Technology (BNRist)（北京国家信息科学技术研究中心（BNRist））；Department of Computer Science and Technology, Tsinghua University（清华大学计算机科学与技术系）
Integrated Exploration-Aware UAV Route Optimization and Path Planning
Department of Aerospace Engineering, University of Michigan（密歇根大学航空航天工程系）；Department of Electrical Engineering, Brigham Young University（BYU 电子工程系）；Department of Aerospace Engineering, Department of Civil and Environmental Engineering, and Department of Industrial and Operations Engineering, University of Michigan（密歇根大学航空航天工程系、土木与环境工程系和工业与运营管理工程系）
