An Overview of Next-Generation Underwater Target Detection and Tracking: An Integrated Underwater Architecture <s> B. REMOTELY OPERATED VEHICLES (ROVs) <s> The power supply for unmanned underwater vehicles has been an important research point since the vehicles were invented. The power systems and environmental energy conversions for the vehicles are reviewed in the paper. Several topics are represented: problems and general solutions for unmanned underwater vehicles power supplies; the mechanisms and structures of tether power system; characteristics of several batteries; the characterization of potential environmental energy, and energy conversion for unmanned underwater vehicles. Docking stations for underwater vehicles continuation are also represented in the paper. Some typical vehicles powered by the power systems and their performances are listed and analyzed. <s> BIB001 </s> An Overview of Next-Generation Underwater Target Detection and Tracking: An Integrated Underwater Architecture <s> B. REMOTELY OPERATED VEHICLES (ROVs) <s> Autonomous Underwater Vehicles (AUVs) have a wide range of applications in marine geoscience, and are increasingly being used in the scientific, military, commercial, and policy sectors. Their ability to operate autonomously of a host vessel makes them well suited to exploration of extreme environments, from the World’s deepest hydrothermal vents to beneath polar ice sheets. They have revolutionized our ability to image the seafloor, providing higher resolution seafloor mapping data than can be achieved from surface vessels, particularly in deep water. This contribution focuses on the major advances in marine geoscience that have resulted from AUV data. The primary applications are i) submarine volcanism and hydrothermal vent studies, ii) mapping and monitoring of low-temperature fluid escape features and chemosynthetic ecosystems, iii) benthic habitat mapping in shallow- and deep-water environments, and iv) mapping of seafloor morphological features (e.g. bedforms generated beneath ice or sediment-gravity flows). A series of new datasets are presented that highlight the growing versatility of AUVs for marine geoscience studies, including i) multi-frequency acoustic imaging of trawling impacts on deep-water coral mounds, iii) collection of high-resolution seafloor photomosaics at abyssal depths, and iii) velocity measurements of active submarine density flows. Future developments in AUV technology of potential relevance to marine geoscience include new vehicles with enhanced hovering, long endurance, extreme depth, or rapid response capabilities, while development of new sensors will further expand the range of geochemical parameters that can be measured. <s> BIB002 </s> An Overview of Next-Generation Underwater Target Detection and Tracking: An Integrated Underwater Architecture <s> B. REMOTELY OPERATED VEHICLES (ROVs) <s> Important seafloor applications, including mine countermeasures, unexploded ordnance (UXO) surveys, salvage, and underwater pipeline and cable tracking, require the detection, geo-registration, and characterization of man-made targets on, or below, the seafloor. Investigations in littoral environments can be time-consuming and expensive due to the challenges of accurately tracking underwater assets, the difficulty of quick or effective site reconnaissance activities, high levels of clutter in nearshore areas, and lack of situational awareness and real-time feedback to operators. Consequently, a high payoff exists for effective methods using sensor and data fusion, feature extraction, and effective payload integration and deployment for improved assessments of littoral infrastructure. In this paper, we present technology development and demonstration results from multiple US DOD-funded projects over the last 4 years that have been focused on advancing seafloor target detection, tracking, and classification for specific environmental and defense missions. We focus on challenges overcome in integrating and testing new three-dimensional controlled-source electromagnetic sensors on a variety of remotely and autonomously operated sensing platforms (ROVs, AUVs and bottom crawling systems). Results from nearshore (surf zone and marsh in North Carolina) and offshore reef experiments (Lower Florida Keys) are presented. In particular, we discuss test results two different systems deployed for shallow hazard and infrastructure applications. The first system is directly integrated with ROV systems and consists of a low-profile multi-channel electromagnetic (EM) sensor coupled with a high-resolution stereo camera pair and other auxiliary sensors. The second system is based on a tow sled pulled from a robotic crawler tailored for onshore/offshore use and ruggedized for operations in challenging surf zone conditions. Performance results from tests conducted offshore in the Florida Keys and off the Outer Banks of North Carolina show great promise for utility of these integrated systems for a variety of applications. This includes pilot studies of both bottom crawling and hydraulically propelled/swimming AUV's with integrated EM sensing systems with seafloor test objects. Metrics such as system mobility, autonomy, detection localization, and target discrimination against clutter and environmental noise are analyzed. <s> BIB003 </s> An Overview of Next-Generation Underwater Target Detection and Tracking: An Integrated Underwater Architecture <s> B. REMOTELY OPERATED VEHICLES (ROVs) <s> A critical challenge for autonomous underwater vehicles (AUVs) is the docking operation for applications such as sleeping under the mother ship, recharging batteries, transferring data, and new mission downloading. The final stage of docking at a unidirectional docking station requires the AUV to approach while keeping the pose (position and orientation) of the vehicle within an allowable range. The appropriate pose therefore demands a sensor unit and a control system that have high accuracy and robustness against disturbances existing in a real-world underwater environment. This paper presents a vision-based AUV docking system consisting of a 3D model-based matching method and Real-time Multi-step Genetic Algorithm (GA) for real-time estimation of the robot’s relative pose. Experiments using a remotely operated vehicle (ROV) with dual-eye cameras and a separate 3D marker were conducted in a small indoor pool. The experimental results confirmed that the proposed system is able to provide high homing accuracy and robustness against disturbances that influence not only the captured camera images but also the movement of the vehicle. A successful docking operation using stereo vision that is new and novel to the underwater vehicle environment was achieved and thus proved the effectiveness of the proposed system for AUV. <s> BIB004
ROVs are human-controlled and tether-dependent vehicles that remain tethered to the source vessel and used mostly in applications where continuous supervision of manpower is required. These vehicles are generally equipped with cameras and can travel in the ocean as far as their tether let; therefore, they are mostly used in applications where visual information is required. They have continuous power sources used for both electrical power and communications BIB001 . Due to their tethered factor, ROVs draw more power and noise, and can communicate real-time data BIB002 . They move with less speed and have limited spatial range than AUV. They have high risks of tether's failure and are heavy weight vehicles due to the requirement of tether management system (TMS). They have high turning times typically of 4 -6 hours  . A 3D modelbased matching method and Real-time Multi-step Genetic Algorithm (GA) for vision-based real-time estimation of target's position and orientation by using a ROV is presented in BIB004 . The experimental results conducted in a pool showed that the system is robust and accurate enough to overcome environmental hindrances that not only affect the images but also the vehicular movement. An integrating scheme is proposed in BIB003 to emphasize the challenges of deploying, developing, and testing 3D electromagnetic sensors on different ROVs and AUVs. The objective is to enhance target detection, tracking, and classification for specific underwater defense scenarios and missions.