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Autonomous surface vehicles (ASVs) are becoming more and more popular for performing hydrographic and navigational tasks. One of the key aspects of autonomous navigation is the need to avoid collisions with other objects, including shore structures. During a mission, an ASV should be able to automatically detect obstacles and perform suitable maneu...
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We report a catastrophic landslide occurred in Gokseong County, South Korea, on August 7, 2020. Torrential rain, with a cumulative rainfall of more than 250 mm for the preceding 3 days, contributed as a trigger or a primer to an initiation of slope failure and ensuing evolution to a debris flow. The runout length, area, and volume of the Gokseong l...
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... The digital camera can capture land cover images with a spatial resolution of 1.55 µm and an image size of 4000 × 3000 pixels. The camera tagged (into the EXIF metadata) the images with geolocation data using the UAV's GPS (direct image georeferencing) [34]. The survey flight plan was programmed using DroneDeploy software (version 5.45.0), with input parameters including post-flight geodetic grade ground control point (GCP) measurements, the UTM cartographic projection system, and the WGS 84/Pseudo Mercator reference datum. ...
... The flight path followed a single-grid mission plan and was used for general measurements with a nadir camera orientation. This plan is suitable for most environments and is recommended when the principal interest is in 2D map outputs, relatively flat surfaces, and large areas [34]. ...
Sugarcane crops have a long cycle with successive harvests before re-planting, and row gaps are one of the main problems associated with the yield. The objective of this study was to establish an alternative methodology for measuring the planting and regrowth of sugarcane rows using UAV (Unmanned Aerial Vehicle) images and to compare it with manual measurements. This study was conducted in a 1 ha experimental area under mechanized harvesting. The reference methodology consists of measuring the continuous distances without regrowth between two plants along a planting row, considering distances greater than 0.50 m as gaps and the following gaps classes: >0.5–1.0 m, >1.0–1.5 m, >1.5–2.0 m, >2.0–3.5 m, and >3.5 m. Images were collected from a UAV equipped with a 12-megapixel RGB camera. The number of regrowth gaps measured through imaging for the class of gaps with a length between 0.5 and 1.0 m was eight times higher than field measurement. In the class of gaps with a length between 1.0 and 1.5 m, the result is the opposite, as the field measurement was approximately three times higher than the UAV measurement, with a significant difference in both classes. In the other length classes analyzed, the number of gaps did not show significant differences. Our results suggest that regrowth gaps can be quickly estimated with the proposed methodology for gaps greater than 1.5 m. For gaps smaller than <1 m, the methodology using a UAV is not accurate.
... In underwater operations, these vehicles typically use sonar and acoustic communication systems to navigate and gather data, thus overcoming the challenges faced in the underwater environment [90,91]. Surface and aerial autonomous vehicles use advanced navigation systems such as the global positioning system (GPS) and radar to perform navigation [92][93][94][95]. The operational range of these vehicles can be extended by using energy storage technologies with higher capacities, e.g., high-capacity batteries, or by utilizing renewable energy sources [96][97][98][99]. ...
In ocean engineering, engineering principles are applied to the ocean domain. Advanced technology is facilitating efficient exploration of oceanic regions with minimal human intervention, and autonomous vehicles are increasingly used to automate various ocean engineering tasks. However, using fully autonomous vehicles raises ethical and legal concerns that must be properly regulated. Nowadays, the most common applications of autonomous vehicles in the ocean domain include infrastructure maintenance, underwater mapping, resource exploration, environmental monitoring, and various military operations such as mine warfare (MW) and intelligence, surveillance, and reconnaissance (ISR). This article explores the prevalent applications of autonomous vehicles in ocean engineering, analyzing existing regulations, liability and accountability issues, data privacy, cybersecurity challenges, and interoperability. Through a Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis, it was possible to better understand the current state of using autonomous vehicles in ocean engineering and develop a possible future strategy in the field. To make the usage of autonomous vehicles more reliable in ocean engineering, it is essential to advance them technologically and update the existing laws that deal with these kinds of applications.
... Vessels of this type are unmanned surface vehicles which, by means of the installed survey equipment, are capable of carrying out hydrographic surveys [7][8][9]. They are also capable of carrying out surveys thanks to their apparatus, including a vertical or a multi-beam echo sounder, a GNSS positioning system, sonars, LiDAR (Light Detection and Ranging), and a digital camera [10,11]. In addition, unmanned vessels enable the exploration of seabed topography, water area depths, and other parameters of the marine environment. ...
... In conclusion, it should be stated that the particular features which distinguish USVs from classic survey vessels (hydrographic cutters and vessels) include their small size and the shallow draught (up to 20 cm), which enables the exploration of water areas that are difficult to access, and, in particular, areas with a depth of even less than 1 m, which are inaccessible to typical hydrographic vessels [11,20]. For this reason, their ability to carry out a quick bottom inspection, without unnecessary time delays and preparations, independently and at any time, is a unique feature of USVs. ...
In contrast to classic hydrographic cutters, unmanned surface vehicles, due to their size, ease of transport and the equipment installed, enable the performance of quick and cost-effective bottom inspections in various water areas. Thanks to their shallow draught and high manoeuvrability, hydrographic drones are capable of the bathymetric exploration of shallow waters such as harbours, hydrotechnical structures and the areas where classic naval vessels could encounter implementation difficulties. The aim of this paper is to demonstrate, using a selected practical example, the specific ability of an unmanned surface vehicle (USV) to carry out the urgent and immediate inspection of the bottom of a specific water area. The freedom to move between restricted areas, the ease of transport and the satisfactory quality of the surveys make hydrographic drones ideal tools for projects of this type. The referenced study produced a bathymetric map of a section of the seabed adjacent to the quay at which a Search and Rescue (SAR) vessel is moored and regularly, at its permanent fixed location, actuates its propellers. The effect of its propellers is the local deepening of the bottom in two places. The research showed a local decrease in the depth from 5.5 m to less than 7 m, which may threaten the stability of the quay structure. In addition, it was noted that the washed bottom material had been moved approximately 10 m from the quay, causing shallowing in two places and reducing the depth from 5.5 m to 4.7 m. This study demonstrated that the use of USVs for applications of this type is very effective in terms of the implementation time and is economically justified.
... Researchers are now exploring unmanned surface vehicles (USVs) as a novel approach to improve resolution and capabilities of maritime radar systems [12]. USVs, autonomous vehicles operating across terrains [13], are proven effective in surveillance and monitoring [14]- [16], widely used in civilian and military domains. In radar detection, bistatic radar implementation, eliminating bulky machinery [3], has promising results. ...
A traditional maritime radar system is utilized for ship detection and tracking through onshore transmitters and receivers. However, it faces challenges when it comes to detecting small boats. In contrast, unmanned surface vehicles (USVs) have been designed to monitor maritime traffic. They excel in detecting vessels of various sizes and enhance the capabilities and resolution of maritime radar systems. Nevertheless, just like conventional radar systems, USVs encounter difficulties due to environmental interference and clutter, affecting the accuracy of target signal detection. This research proposes a comprehensive numerical assessment to tackle the clutter issue associated with USVs. This involves gathering clutter signal data, performing numerical analysis, and employing distribution fitting techniques that leverage mathematical distributions to unravel data complexity. The root mean square error (RMSE) is applied in this analysis to validate the efficacy of the distribution model. The results of this study aim to formulate a clutter model that can enhance radar performance in detecting small vessels within cluttered environments.
... However, because of the large size of these devices, it is difficult to install them on small autonomous vehicles. In [33], the authors tested the radar used in autonomous cars in the marine environment. Unfortunately, the achieved range of the system (approximately 100 m) means that it can only affect collision avoidance. ...
Autonomous Underwater Vehicles (AUVs) are currently one of the most intensively developing branches of marine technology. Their widespread use and versatility allow them to perform tasks that, until recently, required human resources. One problem in AUVs is inadequate navigation, which results in inaccurate positioning. Weaknesses in electronic equipment lead to errors in determining a vehicle’s position during underwater missions, requiring periodic reduction of accumulated errors through the use of radio navigation systems (e.g., GNSS). However, these signals may be unavailable or deliberately distorted. Therefore, in this paper, we propose a new computer vision-based method for estimating the position of an AUV. Our method uses computer vision and deep learning techniques to generate the surroundings of the vehicle during temporary surfacing at the point where it is currently located. The next step is to compare this with the shoreline representation on the map, which is generated for a set of points that are in a specific vicinity of a point determined by dead reckoning. This method is primarily intended for low-cost vehicles without advanced navigation systems. Our results suggest that the proposed solution reduces the error in vehicle positioning to 30–60 m and can be used in incomplete shoreline representations. Further research will focus on the use of the proposed method in fully autonomous navigation systems.
... This type of four-wheeled vehicle, type H-1, is an MPV type car that is very suitable to be used as a family car because of its large size and spaciousness, so it can accommodate the family just for walking around or going on holiday somewhere. This type of H-1 four-wheeled vehicle has a newer design and carries contemporary technology, namely a head unit screen that looks floating [6]. Even though it looks big, this car still has a very good exterior design and is not inferior to the design of other MPV cars. ...
... Data processing was taken 6 months from Jan-23 to Jun-23 to make the Pareto diagram after improvement using Minitab software. This control step takes the form of calculating the sigma level after improvement using formulas (2), (3), (4), (5), and (6), and then measuring COPQ after improvement using formula (7), (8), and (9). The next step is to create four-block diagram processes using Visio software. ...
The current era provides challenges for several automotive industries to be able to compete and maintain the quality of their products. For four-wheeled automotive companies, satisfying customers regarding the visual appearance of the vehicle body is very important. However, internally, automotive companies still found many defects or failures in painting, amounting to 32.6%. Apart from that, rework also results in additional costs that the company must incur during the painting process. This study aims to clarify types of painting defects, analyze root causes, provide solutions, improve process capabilities, and increase the sigma level in the painting process in the four-wheeled vehicle industry. This study uses the Lean Six Sigma method, which is integrated into the DMAIC approach and other improvement tools. As a result, this study clarifies four critical defects in the orange peel defects of the painting section, craters, melting, and blur. This study has resulted in several corrective action solutions, including tightening supervision of the performance of painting section operators so that they are consistent and committed to working according to the Standard Operational Procedure (SOP) or work instructions that have been created. A competency matrix is used to evaluate operator performance, which is reported to superiors and subordinates by the supervisory department. After carrying out corrective action, this study increased the process capability from 1.17 to 1.92. The higher the capability value, the higher the sigma level. This study also has increased the sigma level from 2.76 to 3.42, meaning an increase of 78%. .
... Leo Stanislas et al. [6] proposed a LiDAR-based marine target localization system and its calibration strategy for constructing 3D obstacle maps, which was validated in the Maritime RobotX Challenge and achieved spatial localization accuracy of 0.2 m. Andrzej Stateczny et al. [7] proposed a LiDAR-based detection method for coastal structures and obstacles, which effectively avoids collision problems during ship docking, with an average repeated measurement error of 1.19 m in the 100 m range. Jungwook Han et al. [8] proposed a LiDAR-equipped vehicle to improve autonomous navigation capability, which was able to achieve the location and trajectory of obstacle targets within 700 m, with an estimation error of nearly 20 m. ...
As the key route detection device, the performance of marine LiDAR in harsh environments is of great importance. In this paper, a metric reliability analysis method for marine LiDAR systems under extreme wind loads is proposed. First, a static measurement accuracy evaluation model for the LiDAR system is proposed, targeting the problem that the LiDAR measurement tail reduces the measurement accuracy. Second, the distribution of extreme wind speeds in the Pacific Northwest is investigated, and a wind load probability model is developed. Finally, the impact of hull fluctuations on LiDAR measurement accuracy is analyzed by performing hull fluctuation simulations based on the wind load probability model, and the relationship curve between the metric reliability and measurement accuracy of marine LiDAR systems under extreme wind loads is addressed using the Monte-Carlo method. Experimental results show that the proposed LiDAR static measurement accuracy evaluation model can improve the measurement accuracy by more than 30%. Meanwhile, the solved curve of the LiDAR metric reliability versus the measurement allowable error indicates that the metric reliability can reach above 0.89 when the allowable error is 60 mm, which is instructive for the reliable measurement of marine LiDAR systems during ship navigation.
... This allows them, in contrast to manned hydrographic vessels, to carry out bathymetric measurements on shallow water areas with depths of up to 1 m. The system will use a hydrographic "HydroDron" USV ( Figure 6b) [58,59], built during the implementation of a research project entitled "Development of an autonomous/remotely controlled surface platform dedicated to hydrographic surveys in restricted waterbodies", funded by the NCBR in Poland under the INNOSBZ programme [60]. This is undoubtedly a solution that meets the highest global standards for the performance of hydrographic surveys. ...
This publication is aimed at developing a concept of an innovative system for dimension-ing and predicting changes in the coastal zone topography using Unmanned Aerial Vehicles (UAVs) and Unmanned Surface Vehicles (USVs). The 4DBatMap system will consist of four components: 1. Measurement data acquisition module. Bathymetric and photogrammetric measurements will be carried out with a specific frequency in the coastal zone using a UAV equipped with a Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS), Light Detection And Ranging (Li-DAR) and a photogrammetric camera, as well as a USV equipped with a GNSS Real Time Kinematic (RTK) receiver and a MultiBeam EchoSounder (MBES). 2. Multi-sensor geospatial data fusion module. Low-altitude aerial imagery, hydrographic and LiDAR data acquired using UAVs and USVs will be integrated into one. The result will be an accurate and fully covered with measurements terrain of the coastal zone. 3. Module for predicting changes in the coastal zone topography. As part of this module, a computer application will be created, which, based on the analysis of a time series, will determine the optimal method for describing the spatial and temporal variability (long-term trend and seasonal fluctuations) of the coastal zone terrain. 4. Module for imaging changes in the coastal zone topography. The final result of the 4DBatMap system will be a 4D bathymetric chart to illustrate how the coastal zone topography changes over time.
... Ship identification means vessel detecting, recognising and matching the existing data on units capable of navigating specified areas. There are several ways to identify a vessel, depending on specific needs: dedicated Automatic Identification System (AIS) transponders [1], radar systems [2] for tracking and tracing, Long-Range Identification and Tracking (LRIT) that uses voice communication to confirm identity [3], etc. However, visual confirmation is vital in many cases, and onshore video surveillance systems play that part. ...
The identification of ships plays a crucial role in security and managing vessel traffic for ports and onshore facilities. Existing video monitoring systems help visually identify a vessel where other systems are not present or sufficient. Readable vessel plates and hull inscriptions of detected ships in the video stream allow using text location and recognition methods to obtain ships’ identification names or numbers. The obtained information can be then matched with available ship registers. The automation of the process has met many challenges related to the often-low quality of available video streams, heterogeneous regulations on the marking of ships, and the specifics of natural scene text recognition, such as quickly alternating imaging conditions or the interference of the background. The main contribution of this research is a method that can identify any type of vessel in an image that has visible inscriptions (name, registration number) placed on the hull and must be registered in a public registry. The proposed method works with low-quality images with inscriptions placed under different angles and different, readable sizes. Our method recognised 91% of vessels from our test dataset. Obtained identification times have not exceeded 1s. The quality and efficiency of the proposed solution indicate that it is suitable for practical implementation in onshore monitoring systems.
... One of the most important roles of USVs are hydrographic measurements: port basins, lakes, rivers and small reservoirs, whose aim is to measure the seafloor relief with the appropriate accuracy. In addition, USVs are increasingly used for tasks related to supporting the navigation process [25], in underwater photogrammetry [26], or in geological works [27]. ...
Bathymetric surveys performed using small, unmanned vessels are increasingly used in coastal areas and regions difficult to access by hydrographic motorboats. Their geometric dimensions, manoeuvring parameters, low labour intensity, and costs of survey execution have allowed the unmanned survey vessel (USV) to be a commonly recognised surveying platform. It is equipped with a navigation system for positioning, maintaining a course or survey line, determining spatial orientation, and measuring depths. The operation zone of the global navigation satellite system (GNSS) in coastal water regions enables geodetic positioning in land-based surveys and of moving objects, also including, for example, a sounding vessel. Under difficult observational conditions, the positioning is limited by the obscuration of the upper hemisphere, i.e., the visibility of satellites and the reflection from high field buildings. This poses a threat to a small vessel operating at a very short distance from a hydro-engineering structure. Based on a study performed in a marina, the article presents the determination of the minimum safe distance of the planned survey line to the quay in terms of the USV’s dimensions under good sounding conditions. These include low and constant velocity and good observational conditions for a GNSS receiver. The analysis was conducted on survey lines perpendicular to the quay, which was approached twice at distances of 1–5 m, with a 0.5 m interval. A 1 m distance between the end of the survey line and the quay has been determined for the safety of USV’s navigation and continuity of geospatial data collection during bathymetric surveys.
