1,873 research outputs found
Optimal scheduling for refueling multiple autonomous aerial vehicles
The scheduling, for autonomous refueling, of multiple unmanned aerial vehicles (UAVs) is posed as a combinatorial optimization problem. An efficient dynamic programming (DP) algorithm is introduced for finding the optimal initial refueling sequence. The optimal sequence needs to be recalculated when conditions change, such as when UAVs join or leave the queue unexpectedly. We develop a systematic shuffle scheme to reconfigure the UAV sequence using the least amount of shuffle steps. A similarity metric over UAV sequences is introduced to quantify the reconfiguration effort which is treated as an additional cost and is integrated into the DP algorithm. Feasibility and limitations of this novel approach are also discussed
Ultra Reliable UAV Communication Using Altitude and Cooperation Diversity
The use of unmanned aerial vehicles (UAVs) that serve as aerial base stations
is expected to become predominant in the next decade. However, in order for
this technology to unfold its full potential it is necessary to develop a
fundamental understanding of the distinctive features of air-to-ground (A2G)
links. As a contribution in this direction, this paper proposes a generic
framework for the analysis and optimization of the A2G systems. In contrast to
the existing literature, this framework incorporates both height-dependent path
loss exponent and small-scale fading, and unifies a widely used
ground-to-ground channel model with that of A2G for analysis of large-scale
wireless networks. We derive analytical expressions for the optimal UAV height
that minimizes the outage probability of a given A2G link. Moreover, our
framework allows us to derive a height-dependent closed-form expression and a
tight lower bound for the outage probability of an \textit{A2G cooperative
communication} network. Our results suggest that the optimal location of the
UAVs with respect to the ground nodes does not change by the inclusion of
ground relays. This enables interesting insights in the deployment of future
A2G networks, as the system reliability could be adjusted dynamically by adding
relaying nodes without requiring changes in the position of the corresponding
UAVs
A survey on fractional order control techniques for unmanned aerial and ground vehicles
In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade
A review of relay network on UAVS for enhanced connectivity
One of the best evolution in technology breakthroughs is the Unmanned Aerial Vehicle (UAV). This aerial system is able to perform the mission in an agile environment and can reach the hard areas to perform the tasks autonomously. UAVs can be used in post-disaster situations to estimate damages, to monitor and to respond to the victims. The Ground Control Station can also provide emergency messages and ad-hoc communication to the Mobile Users of the disaster-stricken community using this network. A wireless network can also extend its communication range using UAV as a relay. Major requirements from such networks are robustness, scalability, energy efficiency and reliability. In general, UAVs are easy to deploy, have Line of Sight options and are flexible in nature. However, their 3D mobility, energy constraints, and deployment environment introduce many challenges. This paper provides a discussion of basic UAV based multi-hop relay network architecture and analyses their benefits, applications, and tradeoffs. Key design considerations and challenges are investigated finding fundamental issues and potential research directions to exploit them. Finally, analytical tools and frameworks for performance optimizations are presented
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