Recently, unmanned aerial vehicles (UAVs) attracted significant popularity in both military and civilian domains for various applications and services. Moreover, UAV-aided wireless sensor networks (UAWSNs) became one of the interesting hot research topics. This is mainly because UAWSNs can significantly increase the network coverage and energy utilization compared to traditional wireless sensor networks (WSNs). However, the high mobility, dynamic path, and variable altitude of UAVs can cause not only unforeseen changes in the network topology but also connectivity and coverage problems, which can affect the routing performance of the network. Therefore, the design of a routing protocol for UAWSNs is a critical task. In this paper, the routing protocols for UAWSNs are extensively investigated and discussed. Firstly, we classify the existing routing protocols based on different network criteria. They are extensively reviewed and compared with each other in terms of advantages and limitation, routing metrics and policies, characteristics, difference performance factors, and different performance optimization factors. Furthermore, open research issues and challenges are summarized and discussed.
Recently, owing to the high mobility and low cost of drones, drone-based delivery systems have shown considerable potential for ensuring flexible and reliable parcel delivery. Several crucial design issues must be considered to design such systems, including route planning, payload weight consideration, distance measurement, and customer location. In this paper, we present a survey of emerging drone routing algorithms for drone-based delivery systems, emphasizing three major drone routing aspects: trajectory planning, charging, and security. We focus on practical design considerations to ensure efficient, flexible, and reliable parcel delivery. We first discuss the potential issues arising when designing such systems. Next, we present a novel taxonomy based on the above-mentioned three aspects. We extensively review each algorithm for drone routing in terms of key features and operational characteristics. Furthermore, we compare the algorithms in terms of their main idea, advantages, limitations, and performance aspects. Finally, we present open research challenges to motivate further research in this field. In particular, we focus on the major aspects that researchers and engineers need to consider in order to design effective and reliable drone routing algorithms for drone-based delivery systems.
In recent years, unmanned aerial vehicles (UAVs), commonly known as drones, have gained increasing interest in both academia and industries. The evolution of UAV technologies, such as artificial intelligence, component miniaturization, and computer vision, has decreased their cost and increased availability for diverse applications and services. Remarkably, the integration of computer vision with UAVs provides cutting-edge technology for visual navigation, localization, and obstacle avoidance, making them capable of autonomous operations. However, their limited capacity for autonomous navigation makes them unsuitable for global positioning system (GPS)-blind environments. Recently, vision-based approaches that use cheaper and more flexible visual sensors have shown considerable advantages in UAV navigation owing to the rapid development of computer vision. Visual localization and mapping, obstacle avoidance, and path planning are essential components of visual navigation. The goal of this study was to provide a comprehensive review of vision-based UAV navigation techniques. Existing techniques have been categorized and extensively reviewed with regard to their capabilities and characteristics. Then, they are qualitatively compared in terms of various aspects. We have also discussed open issues and research challenges in the design and implementation of vision-based navigation techniques for UAVs.
A flying ad hoc network (FANETs), also known as a swarm of unmanned aerial vehicles (UAVs), can be deployed in a wide range of applications including surveillance, monitoring, and emergency communications. UAVs must perform real-time communication among themselves and the base station via an efficient routing protocol. However, designing an efficient multihop routing protocol for FANETs is challenging due to high mobility, dynamic topology, limited energy, and short transmission range. Recently, owing to the advantages of multi-objective optimization, Q-learning (QL)-based position-aware routing protocols have improved the performance of routing in FANETs. In his article, we provide a comprehensive review of existing QL-based position-aware routing protocols for FANETs. We rigorously address dynamic topology, mobility models, and the relationship between QL and routing in FANETs, and extensively review the existing QL-based position-aware routing protocols along with their advantages and limitations. Then, we compare the reviewed protocols qualitatively in terms of operational features, characteristics, and performance metrics. We also discuss important open issues and research challenges with potential research directions.
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