A Survey on Energy Optimization Techniques in UAV-Based Cellular Networks: From Conventional to Machine Learning Approaches

Wireless communication networks have been witnessing an unprecedented demand due to the increasing number of connected devices and emerging bandwidth-hungry applications. Albeit many competent technologies for capacity enhancement purposes, such as millimeter wave communications and network densification, there is still room and need for further capacity enhancement in wireless communication networks, especially for the cases of unusual people gatherings, such as sport competitions, musical concerts, etc. Unmanned aerial vehicles (UAVs) have been identified as one of the promising options to enhance the capacity due to their easy implementation, pop up fashion operation, and cost-effective nature. The main idea is to deploy base stations on UAVs and operate them as flying base stations, thereby bringing additional capacity to where it is needed. However, because the UAVs mostly have limited energy storage, their energy consumption must be optimized to increase flight time. In this survey, we investigate different energy optimization techniques with a top-level classification in terms of the optimization algorithm employed; conventional and machine learning (ML). Such classification helps understand the state of the art and the current trend in terms of methodology. In this regard, various optimization techniques are identified from the related literature, and they are presented under the above mentioned classes of employed optimization methods. In addition, for the purpose of completeness, we include a brief tutorial on the optimization methods and power supply and charging mechanisms of UAVs. Moreover, novel concepts, such as reflective intelligent surfaces and landing spot optimization, are also covered to capture the latest trend in the literature.Comment: 41 pages, 5 Figures, 6 Tables. Submitted to Open Journal of Communications Society (OJ-COMS

Collaborative autonomy in heterogeneous multi-robot systems

As autonomous mobile robots become increasingly connected and widely deployed in different domains, managing multiple robots and their interaction is key to the future of ubiquitous autonomous systems. Indeed, robots are not individual entities anymore. Instead, many robots today are deployed as part of larger fleets or in teams. The benefits of multirobot collaboration, specially in heterogeneous groups, are multiple. Significantly higher degrees of situational awareness and understanding of their environment can be achieved when robots with different operational capabilities are deployed together. Examples of this include the Perseverance rover and the Ingenuity helicopter that NASA has deployed in Mars, or the highly heterogeneous robot teams that explored caves and other complex environments during the last DARPA Sub-T competition. This thesis delves into the wide topic of collaborative autonomy in multi-robot systems, encompassing some of the key elements required for achieving robust collaboration: solving collaborative decision-making problems; securing their operation, management and interaction; providing means for autonomous coordination in space and accurate global or relative state estimation; and achieving collaborative situational awareness through distributed perception and cooperative planning. The thesis covers novel formation control algorithms, and new ways to achieve accurate absolute or relative localization within multi-robot systems. It also explores the potential of distributed ledger technologies as an underlying framework to achieve collaborative decision-making in distributed robotic systems. Throughout the thesis, I introduce novel approaches to utilizing cryptographic elements and blockchain technology for securing the operation of autonomous robots, showing that sensor data and mission instructions can be validated in an end-to-end manner. I then shift the focus to localization and coordination, studying ultra-wideband (UWB) radios and their potential. I show how UWB-based ranging and localization can enable aerial robots to operate in GNSS-denied environments, with a study of the constraints and limitations. I also study the potential of UWB-based relative localization between aerial and ground robots for more accurate positioning in areas where GNSS signals degrade. In terms of coordination, I introduce two new algorithms for formation control that require zero to minimal communication, if enough degree of awareness of neighbor robots is available. These algorithms are validated in simulation and real-world experiments. The thesis concludes with the integration of a new approach to cooperative path planning algorithms and UWB-based relative localization for dense scene reconstruction using lidar and vision sensors in ground and aerial robots

Military mimicry:the art of concealment, deception, and imitation

Three dominant thematics emerge from the biological mimicry and camouflage literature, namely, concealment, deception, and imitation. These phenomena are interesting in their own right, but conceptually have similar analogs in the military context that have attracted only minimal intellectual curiosity. Accordingly, the purpose of this paper is to apply biological mimicry and camouflage concepts to the military environment. Concealment in the form of camouflage is traced from its nineteenth century origins to the military's imminent twenty-first century perfection of an “invisibility cloak”. Military deception is the art of duping enemies with fakes and dummies. Finally, imitation is examined from three perspectives: firstly, replacement of military personnel with animals; secondly, exploration of bioengineering, including exploitation of avian aerodynamics, insect biophysical structures, and mammal sonar attributes; and, thirdly, Artificial Intelligence that is driving military mimicry along an evolutionary path towards robots, swarms, and avatars in an emerging and novel military technology revolutio

Optimization and Communication in UAV Networks

UAVs are becoming a reality and attract increasing attention. They can be remotely controlled or completely autonomous and be used alone or as a fleet and in a large set of applications. They are constrained by hardware since they cannot be too heavy and rely on batteries. Their use still raises a large set of exciting new challenges in terms of trajectory optimization and positioning when they are used alone or in cooperation, and communication when they evolve in swarm, to name but a few examples. This book presents some new original contributions regarding UAV or UAV swarm optimization and communication aspects

A Comprehensive Survey of the Tactile Internet: State of the art and Research Directions

The Internet has made several giant leaps over the years, from a fixed to a mobile Internet, then to the Internet of Things, and now to a Tactile Internet. The Tactile Internet goes far beyond data, audio and video delivery over fixed and mobile networks, and even beyond allowing communication and collaboration among things. It is expected to enable haptic communication and allow skill set delivery over networks. Some examples of potential applications are tele-surgery, vehicle fleets, augmented reality and industrial process automation. Several papers already cover many of the Tactile Internet-related concepts and technologies, such as haptic codecs, applications, and supporting technologies. However, none of them offers a comprehensive survey of the Tactile Internet, including its architectures and algorithms. Furthermore, none of them provides a systematic and critical review of the existing solutions. To address these lacunae, we provide a comprehensive survey of the architectures and algorithms proposed to date for the Tactile Internet. In addition, we critically review them using a well-defined set of requirements and discuss some of the lessons learned as well as the most promising research directions

Social work with airports passengers

Social work at the airport is in to offer to passengers social services. The main methodological position is that people are under stress, which characterized by a particular set of characteristics in appearance and behavior. In such circumstances passenger attracts in his actions some attention. Only person whom he trusts can help him with the documents or psychologically

Multi-Robot Systems: Challenges, Trends and Applications

This book is a printed edition of the Special Issue entitled “Multi-Robot Systems: Challenges, Trends, and Applications” that was published in Applied Sciences. This Special Issue collected seventeen high-quality papers that discuss the main challenges of multi-robot systems, present the trends to address these issues, and report various relevant applications. Some of the topics addressed by these papers are robot swarms, mission planning, robot teaming, machine learning, immersive technologies, search and rescue, and social robotics

Improving Operator Recognition and Prediction of Emergent Swarm Behaviors

Robot swarms are typically defined as large teams of coordinating robots that interact with each other on a local scale. The control laws that dictate these interactions are often designed to produce emergent global behaviors useful for robot teams, such as aggregating at a single location or moving between locations as a group. These behaviors are called emergent because they arise from the local rules governing each robot as they interact with neighbors and the environment. No single robot is aware of the global behavior yet they all take part in it, which allows for a robustness that is difficult to achieve with explicitly-defined global plans. Now that hardware and algorithms for swarms have progressed enough to allow for their use outside the laboratory, new research is focused on how operators can control them. Recent work has introduced new paradigms for imparting an operator's intent on the swarm, yet little work has focused on how to better visualize the swarm to improve operator prediction and control of swarm states. The goal of this dissertation is to investigate how to present the limited data from a swarm to an operator so as to maximize their understanding of the current behavior and swarm state in general. This dissertation develops--through user studies--new methods of displaying the state of a swarm that improve a user's ability to recognize, predict, and control emergent behaviors. The general conclusion is that how summary information about the swarm is displayed has a significant impact on the ability of users to interact with the swarm, and that future work should focus on the properties unique to swarms when developing visualizations for human-swarm interaction tasks

Distributing Non-cooperative Object Information in Next Generation Radar Surveillance Systems

Radar surveillance systems, in both airspace and maritime domains, are facing increasing challenges in dealing with objects that cannot be detected by traditional transponder-based radar surveillance technologies. These objects, including birds, weather, Unmanned Aircraft Systems (UAS), hot balloons, are labeled as non-cooperative objects. In order to prevent ambiguity and confusion for human operators using the surveillance data non-cooperative objects are commonly treated as unwanted clutter and removed from the displayed data. However, the omitted information of non-cooperative object can be critical to aircraft safety. With new developments in technology and radar capabilities, it is possible to detect these non-cooperative objects and consider how to distribute relevant information about them to human operators throughout a system. The research goal of this thesis is to identify the human factors challenges in future radar surveillance systems where non-cooperative object information is distributed to both air traffic controllers and pilots. In order to achieve the goal, the thesis first constructed a model of surveillance information distribution in current ATC operations and a model of surveillance information distribution in the expected future operational environment. The expected future surveillance information distribution model was then carefully examined to identify potential human factors challenges in the non-cooperative object information distribution process. Two of the identified challenges (non-equal time delay and information level of details) were studied in depth through conducting human-in-the-loop experiments and online surveys. The results of an asynchronous information (non-equal time delay) static simulation environment experiment showed that while a delay in the non-cooperative object information would lead to observable but not statistically significant longer communication time, it does have a significant effect on number of clarification statements – with an increase of time delay, more clarifications were made. A survey of controller and pilot perceptions of maximum acceptable delay showed no significant differences in the average maximum acceptable delay reported by controller (20.5 seconds) and pilot (13.64 seconds) participants. Future research should consider adopting dynamic simulation environment, subject matter experts and shorter delay intervals to identify an acceptable delay threshold. The survey results also demonstrated that there are more controllers and pilots who have had encounters with UAS in their daily tasks than what was originally expected. The survey also helped identify operational information requirements and availabilities for individual UAS and challenges in sharing non-cooperative object information between controllers and pilots. These findings are quite valuable as they provide guidance on future radar surveillance systems design in supporting the effective distribution of non-cooperative object information. Future work should complete the analysis of the survey and create more dynamic environment for studying information asynchrony