Prototype Design and Experimental Evaluation of Autonomous Collaborative Communication System for Emerging Maritime Use Cases

With the development of technologies related to unmanned vehicles, including unmanned aerial vehicle and unmanned surface vehicle, unmanned vehicles play a pivotal role in maritime management and cruise activities. Meanwhile, lots of evidence shows that a single unmanned vehicle is not qualified for operation under complex environment, whereas the unmanned aerial vehicle–unmanned surface vehicle formation consists of multiple unmanned aerial vehicles and unmanned surface vehicles, which can enhance the performance of the single unmanned vehicle significantly. However, the cooperative operation performance of the unmanned aerial vehicle–unmanned surface vehicle formation is constrained by its communication capacity. Consequently, a cooperative communication framework is designed for the unmanned aerial vehicle–unmanned surface vehicle formation. A distributed dynamic network topology is constructed for fulfilling effective communication for the unmanned aerial vehicle–unmanned surface vehicle formation based on ad hoc network. Experiments are carried out by employing the built unmanned aerial vehicle–unmanned surface vehicle formation platform. Results verify the superiority of the designed cooperative communication framework for the unmanned aerial vehicle–unmanned surface vehicle formation.

Over the past few decades, the usage of unmanned vehicles has grown exponentially, expanding into applications such as the automation of industrial processes and automobiles. However, their utility has often been limited by operational concerns. Fully controlled unmanned vehicles require multiple human operators, while their fully autonomous counterparts lack the ability to handle the complex maneuvers necessary in natural disaster relief and/or search and rescue situations. Semi-autonomous UAVs offer a feasible compromise between the two extremes. In this scenario, an unmanned aerial vehicle (UAV) sends birds-eye images of the terrain beneath it to a computing cluster, which will identify easily traversable terrain and generate a path of least risk to an unmanned ground vehicle (UGV). If the path's risk is below a certain threshold, then the UGV will be permitted to proceed on its own. Otherwise, a human operator will be notified, so that he or she may control the UGV directly until it exits the most dangerous terrain. This paradigm allows a single operator to manage several UAVs simultaneously.

Military-industrial complexes of many countries have invested billions of dollars in the industry over 120 years of development and have achieved significant progresses in the creation of surface, water and underwater equipment. Groups of military unmanned vehicles include unmanned aerial vehicles (UAVs), deck-based UAVs, water, underwater and hybrid unmanned vehicles (UAVs). Their purpose is intelligence, surveillance, strategic research projects, and military transport purposes. As for the civilian use of unmanned vehicles, this is a young industry, it is 15 years old. The beginning of the era of non-military unmanned aerial vehicles (UAVs) and then unmanned floating vehicles (UAVs) is considered to be 2006, when the US Federal Aviation Administration allowed the flights of small custom drones. At the same time, they were given a definition: a device that is remotely controlled by an operator; a device that moves along a pre-planned route. Unmanned vehicles the use of which for the purposes of the forest complex of our country is carried out or is planned to begin in the near future must meet some special requirements that are discussed in this article.

An autonomous unmanned surface vehicle (USV) landing system of vertical takeoff and landing (VTOL) fixed-wing unmanned aerial vehicle (UAV) based on raptor vision is presented in this paper. The color saliency detection method based on raptor vision in the biological raptor vision color resolution space is developed to obtain the landing target and markers in the mission scene. A three-color nested landing target scheme is designed to accommodate the different height of UAV. Considering the various interferences exist in the complex environment, the target occlusion strategy and the go-around (GA) strategy are supplemented in the vision navigation system to improve the accuracy and security of the landing mission. The complete UAV/USV flight verification system is developed to validate the effectiveness of the proposed method. Results show that the autonomous landing system based on raptor vision obtain a quite satisfactory landing outcome. The horizontal errors of UAV autonomous landing are both less than 5cm. The success rate of UAV landing has been greatly improved. Therefore, the proposed autonomous landing system provides a feasible technical pathway for UAV landing on a USV.

The identification and classification of obstacles in navigable and non-navigable regions, as well as the measurement of distances, are crucial topics of investigation in the field of autonomous navigation for unmanned surface vehicles (USVs). Currently, USVs mostly rely on LiDAR and ultrasound technology for the purpose of detecting impediments that exist on water surfaces. However, it is worth noting that these approaches lack the capability to accurately discern the precise nature or classification of those obstacles. Nevertheless, the limited optical range of unmanned vessels hinders their ability to comprehensively perceive the entirety of the surrounding information. A cooperative USV-UAV system is proposed to ensure the visual perception ability of USVs. The multi-object recognition, semantic segmentation, and obstacle ranging through USV and unmanned aerial vehicle (UAV) perspectives are selected to validate the performance of a cooperative USV-UAV system. The you only look once-X (YOLOX) model, the proportional–integral–derivative-NET (PIDNet) model, and distance measurements based on a monocular camera are utilized to realize these problems. The results indicate that by integrating the viewpoints of USVs and UAVs, a collaborative USV-UAV system, employing the aforementioned methods, can successfully detect and classify different objects surrounding the USV. Additionally, it can differentiate between navigable and non-navigable regions for unmanned vessels through visual recognition, while accurately determining the distance between the USV and obstacles.

An unmanned aerial vehicle (UAV) is an aircraft without a human pilot and a type of unmanned vehicle. UAVs controlled with the help of remote controller. Due to increasing demand of UAVs the various researchers developed the new technologies in wireless communication system. This paper majorly concerns over the Analysis and comparison of MANET Routing protocols for UAV communication. UAVs are playing vital roles in mobile ad-hoc networks (MANETs). Routing is most important task when we are conducting the wireless communication among UAVs. In this paper we analyse the performance of different type of mobile ad-hoc network (MANET) protocols for the communication of UAVs. Various research papers over MANET Routing protocols for UAV communication are discussed in this review paper.

The tragic Deepwater Horizon accident in the Gulf of Mexico in 2010 as well as the increase in deepwater offshore activity have increased public interest in counter-measures available for sub-surface releases of hydrocarbons. To arrive at proper contingency planning, response managers urge for a system for instant detection and characterization of accidental releases. Along these lines, this paper describes the application of a heterogeneous robotic system of unmanned vehicles: autonomous underwater vehicle (AUV), unmanned surface vehicle (USV) and unmanned aerial vehicle (UAV) extended with the oil spill numerical modeling, visualisation and decision support capabilities. A first set of field experiments simulating oil spill scenarios with Rhodamine WT was held in Croatia during the early autumn 2014. The objectives of this experiment were to test: effectiveness of the system for underwater detection of hydrocarbons, including multi-vehicle collaborative navigation and communication as well as visualisation of the system components.

Multi-agent formation control is an important part of distributed perception and cooperation, which is convenient to complete various complex tasks and would be a key research direction in the future. This paper reviews the corresponding problems of formation control and the existing centralized and distributed formation control strategies. In particular, we discuss four types of distributed formation control methods based on position and displacement in the global coordinate system and distance and bearing in the nonglobal coordinate system, respectively. Moreover, this paper analyzes affine formation which does not require the global coordinate system. Combined with the current practical applications of multi-agent systems, the latest research for the formation control of the unmanned aerial vehicle (UAV), unmanned ground vehicle (UGV), unmanned surface vehicle (USV) and autonomous underwater vehicle (AUV) is given. Finally, the challenges and opportunities in this burgeoning field are discussed.

Designing and building of the unmanned aircraft, especially light and ultra light vehicles, is mainly performed using the experience gained when constructing the flying models. There have not been uniform principles of building and exploiting of the mini and micro UAV (Unmanned Aerial Vehicle) in the form of regulations similar to those for manned airplanes. The unmanned vehicles of these classes in terms of their abilities and attractive price are more frequently exploited using the same air area as manned airplanes performing missions over the inhabited areas. An urgent necessity arises to work out the norms of flight suitability of the mini and micro unmanned aerial vehicles. The work contains the analysis of suitability of the current aviation regulations to determine the requirements for the mini unmanned vehicles. The work concentrates on the phenomenon of determining the symmetrical loads from the maneuvers and the turbulence atmosphere. The result of this analysis is the Limit Maneuver Envelope, Limit Gust Envelope and Limit Combined Envelope for mini UAV. The analyzed flight states allowed selecting the so called design cases which can become a basis for determining the norms of loading of mini unmanned aerial vehicles which can constitute the beginning of the regulations for building of the unmanned aerial vehicles of this class.

This paper is interested in the problem of monitoring and cleaning dirty zones of oceans, dealing with the notion of path planning for semi-autonomous unmanned vehicles. We present a hybrid cooperative architecture for unmanned aerial vehicle (UAV) to monitor ocean region and clean dirty zones with the help of swarm unmanned surface vehicles (USVs). In the path planning problem, unmanned vehicles must plan their path from the starting to the goal position. In this article, we propose a solution to handle the problem of trajectory planning for semi-autonomous cleaning vehicles. This solution is based on the proposed Genetic Algorithm (GA). In order to optimize this process, our proposed solution detects and reduces the pollution level of the ocean zones while taking into account the problem of fault tolerance related to these vehicles.

Abstract: Path planning is a way to define the motion of an autonomous surface vehicle (ASV) in any existing obstacle environment to enable the vehicle's movement by setting directions to avoid that can react to the obstacles in the vehicle's path. A good, planned path perceives the environment to the extent of uncertainty and tries to build or adapt its change in the path of motion. Efficient path planning algorithms are needed to alleviate deficiencies, which are to be modified using the deterministic path that leads the ASV to reach a goal or a desired location while finding an optimal solution has become a challenge in the field of optimization along with a collision-free path, making path planning a critical thinker. The traditional algorithms have a lot of training and computation, making it difficult in a realistic environment. This review paper explores the different techniques available in path planning and collision avoidance of ASV in a dynamic environment. The objective of good path planning and collision avoidance for a dynamic environment is compared effectively with the existing obstacle’s movement of different vehicles. Different path planning technical approaches are compared with their performance and collision avoidance for unmanned vehicles in marine environments by early researchers. This paper gives us a clear idea for developing an effective path planning technique to overcome marine accidents in the dynamic ocean environment while choosing the shortest, obstacle-free path for Autonomous Surface Vehicles that can reduce risk and enhance the safety of unmanned vehicle movement in a harsh ocean environment.

This paper provides both the core ideas of a heterogeneous marsupial robotic System and the details of the practical aspects related to its hardware architecture and cooperative system structure. This heterogeneous marsupial robotic system is composed by an unmanned surface vehicle (USV) that acts as a carrier and an unmanned aerial vehicle (UAV) that acts as a passenger, and it is designed for military tasks and other tasks like environmental monitoring, wild life tracking, and search & rescue missions. Through the combination, the cooperative marsupial robots benefit from their heterogeneity by using the superiority of each team member and overcoming their limitations. Moreover, the attitude control simulation model of the UAV is built, and the self-adaptive fuzzy parameter tuning rules for PID flight controller are given, so as to realize the online self-tuning of the controller parameters. Simulation results show that: compared with the conventional PID controller, this attitude control algorithm of fuzzy self-adaptive PID has a better dynamic response performance.

The purpose of this paper is to present an ionizing radiation sensor suitable for nanosatellites, small drones and other types of unmanned vehicles. When implemented on an airborne or ground-based unmanned vehicle the sensor is beneficial in disaster management scenarios such as inspection of buildings and facilities for ionizing radiation contamination and measurements of the ionizing radiation dose. Herein, a design and laboratory tests of the sensor are presented. The instrument is a lightweight module having low power consumption suitable for nanosatellite platforms and for mobile use by having it installed in an unmanned system (airborne or ground-based). For test purposes a 36-rotor drone was developed along with a mobile ground based unmanned vehicle. With all implementations the radiological sensor is directly connected to the main processor unit of the platform. In the case of the drone and ground-based vehicle systems the processor unit is the microcontroller of the autopilot. Experimental results of laboratory measurements of different radiation sources are shown and discussed. The experimental setup demonstrates a few advances related to specific problems encountered in the existing ionizing radiation measurement systems.

This work addresses the distributed predefined-time cooperative formation of heterogeneous multiagent systems comprising unmanned surface vehicles (USVs) and unmanned aerial vehicles (UAVs) with inherent dynamic uncertainties. By transforming the model coordinates, the underactuated heterogeneous USV-UAV systems can be converted into a fully actuated second-order multiagent framework. Subsequently, a predefined-time dynamic observer is designed to estimate the uncertain dynamics of each agent. Combining the backstepping method and the virtual leader model, a predefined-time distributed cooperative formation control based on uncertain dynamic estimation is designed for the heterogeneous USV-UAV systems. The convergence of the formation errors is rigorously demonstrated by constructing a suitable Lyapunov function under a predefined time framework. Ultimately, the two numerical cases in both the fixed and time-varying formation scenarios confirm the effectiveness of the constructed method.

With the rapid development of marine networks, there have been growing demands for computation-intensive and delay-sensitive marine applications and services. However, the limited underwater energy supply and the acoustic channels result in the low efficiency for computing tasks and high transmission delay. In this paper, we investigate the unmanned aerial vehicles (UAVs)-assisted multi-access computation offloading in marine networks, with the objective of minimizing the energy consumption of ocean devices. Specifically, for the underwater segment, we consider the scenario that multiple underwater sensor nodes (USNs) covered by the unmanned surface vehicle (USV) upload their sensing data via non-orthogonal multiple access (NOMA) for improving the channel utilization. For the radio frequency segment, we consider the scenario that multiple UAVs hovering in the air act as the aerial edge servers for providing computing services, in which the USV offloads the workloads to UAVs via frequency division multiple access (FDMA) for avoiding their co-channel interference, while taking into account that a malicious node overhears the USV's offloading transmission. To improve the computation offloading efficiency, we formulate an optimization problem for USNs and USV to minimize the total energy consumption by jointly optimizing the USN's uploading time, USV's computation offloading, USV's offloading time, and the secrecy provisioning. Despite the non-convexity of the formulated joint optimization problem, we exploit a layered structure to decompose the problem, and propose efficient algorithms to obtain the optimal solutions. Finally, we conduct simulations to validate the effectiveness and efficiency of the proposed algorithms. Numerical results demonstrate that our algorithms can significantly reduce the energy consumption in comparison with the benchmark schemes.