4차 산업혁명의 도래로 인한 기술혁신은 자율운항선박을 중심으로 해상 운송분야까지 활발한 발전을 불러왔다. 특히, 현재의 선원이 직접 운항하는 방식인 유인선박 사이에서 운항하게 될 자율운항선박은 자율도에 따라 원격제어를 통해 운항을 수행하며, 육상에 서 이를 제어할 원격운항자에 대한 관심 또한 늘어나고 있다. 하지만 아직 원격운항자가 개입이 필요한 상황이 동시에 발생하는 등을 고 려한 원격운항자 최소 인력 요구사항에 대한 연구는 부족한 상황이다. 본 연구는 특정 해역 구간의 누적된 항적데이터를 활용하여 선박 간에 발생할 수 있는 조우상황에서 원격운항자의 개입이 필요한 상황을 정의하고, 해당 구간을 특정 규모의 자율운항선박 선대로 운항하 였을 때, 원격운항자의 개입이 동시에 필요한 상황이 얼마나 발생하는지를 시뮬레이션을 통해 확인하였다. 연구의 결과는 향후 실제 자율 운항선박 선대를 운행할 원격운항센터의 원격운항자의 적정인력 배치 등의 계획 또는 정책 수립에 활용될 기초 자료로 활용될 것으로 기 대한다.

경로추종 제어는 대양에서 선박의 자율운항을 위한 가장 기본적인 연구 중에 하나로 여겨진다. 본 연구는 선수미방향, 횡방향 및 회두방향으로 외력이 작용하는 경로추종 제어를 다룬다. 가상의 선박에서 발생하는 항로를 자선이 추종하는 문제를 해결하기 위해서 유도 원리와 백스테핑 기법을 활용하였다. 경로추종 제어에서 가장 중요한 기술 중에 하나는 오차 동역학에 관한 것으로서, 이 개념은 선박의 자동 충돌 회피 및 자동 접안 제어 등과 같은 연구 영역에서도 활용이 가능하다. 유도 원리와 오차 변수의 알고리즘은 수치 시뮬레이션을 통해 증명하였다. 그 결과, 회두각의 오차를 제외한 대부분의 오차 변수는 제어기를 통하여 제로 값으로 수렴하였다. 기존에 근거리 통항선박의 간섭력을 고려한 안전통항거리의 값보다 두 선박 간의 경로추종 제어의 트래킹 오차의 값이 더 작은 점이 가장 흥미로운 결과 중에 하나로 여겨진다. 또한 프로펠러, 핀이나 러더와 같은 엑츄에이터의 손상을 줄이기 위해서는 수렴의 성능과 선박의 안전을 절충하여 적합한 제어 파라미터를 결정할 필요가 있다.

본 연구는 스마트 자율운항선박(Maritime Autonomous Surface Ship, MASS) 기술 개발 및 실증을 위한 산학 과제로서 목포해양 대학교와 삼성중공업이 함께 참여한 연구가 안전하게 실시되어 질수 있도록 안전관리 절차서를 개발하였다. 본 연구에서는 국내 및 국 제해사기구(International Maritime Organization, IMO)의 관련 가이드라인 및 해사 관련법 검토를 거쳐 안전관리 절차서를 개발하였다. 안전관리 절차서는 자율운항선박의 관련 해당 당국과 이해관계자들이 시스템 및 기반 시설에서 시험의 안전 및 환경 보호와 관련하여 적절하게 실시하기 위하여 국제해사기구에서 제시한 자율운항선박 시험을 위한 지침(MSC.1/Circ.1604, Annex : Interim guidelines for MASS trials)의 의거하여 개발 하였다. 개발된 안전관리 절차서는 당직체제로 운항 중인 선박에 항해보조기기로 탑재한 자율운항요소기술을 적용한 시스템의 해상 실증 시험을 위하여, 대한민국 연안의 해양환경보호와 항행 안전을 준수하면서, 관련 시스템의 시험이 안전하고 안정적으로 수행할 수 있도록 개발되었다.

While IMO’s e-Navigation project’s scope is to enhance safety of navigation by improved shipto- shore-cooperation, the EU’s FP7 project MUNIN’s aim is to develop a concept for an autonomous dry bulk carrier, that is at least as safe as a manned vessel. As e-Navigation has a strong focus on improving the human element in shipping and MUNIN tends towards an unmanned bridge, a common baseline might look quite contradictory at first, but they share the need to ensure and enhance the safety of navigation. After an introduction into e-Navigation and the MUNIN project, this paper will demonstrate with two examples, how MUNIN’s results address identified e-Navigation’s gaps and addresses e-Navigation’s user needs. Thus, MUNIN contributes to the development and implementation of the prioritized e-Navigation solutions.

Technology-driven development of a new system makes it difficult for users and stakeholders to identify or intervene in the development process, resulting in systems with unnecessary functions and poor quality services. Applying the software architecture design process to the initial design of the navigation system platform of autonomous ships enables the development of a system that reflects the required functions and service quality of the stakeholders. The design, which includes all of the subsystems that make up an autonomous ship platform, is close to an enterprise architecture. Thus, we strived to design a navigation system platform suitable for the design range of the software architecture. This study analyzed the definition of functional requirements, and quality attributes by applying the software architecture design procedure. This study was conducted to identify the characteristics of the navigation system and platform needs, and the stakeholders were identified. To derive the functional requirements and constraints of the platform, a quality attributes workshop was held engaging stakeholders, and the results of the analysis of functional requirements and quality attributes were listed. Based on the results of this study, the architect can establish the evidence and technical solutions that are integral for the architecture development, and will facilitate the creation of quality attribute scenarios.

The Global Positioning System (GPS) is widely used to aid the navigation of aerial vehicles. However, the GPS cannot be used indoors, so alternative navigation methods are needed to be developed for micro aerial vehicles (MAVs) flying in GPS-denied environments. In this paper, a real-time three-dimensional (3-D) indoor navigation system and closed-loop control of a quad-rotor aerial vehicle equipped with an inertial measurement unit (IMU) and a low-cost light detection and ranging (LIDAR) is presented. In order to estimate the pose of the vehicle equipped with the two-dimensional LIDAR, an octree-based grid map and Monte-Carlo Localization (MCL) are adopted. The navigation results using the MCL are then evaluated by making a comparison with a motion capture system. Finally, the results are used for closed-loop control in order to validate its positioning accuracy during procedures for stable hovering and waypoint-following.

In this paper we propose the method that detects moving objects in autonomous navigation vehicle using LRF sensor data. Object detection and tracking methods are widely used in research area like safe-driving, safe-navigation of the autonomous vehicle. The proposed method consists of three steps: data segmentation, mobility classification and object tracking. In order to make the raw LRF sensor data to be useful, Occupancy grid is generated and the raw data is segmented according to its appearance. For classifying whether the object is moving or static, trajectory patterns are analysed. As the last step, Markov chain Monte Carlo (MCMC) method is used for tracking the object. Experimental results indicate that the proposed method can accurately detect moving objects.

최근 항공기, 자동차, 선박을 포함하여 다양한 분야에서 무인시스템에 관한 연구 개발이 이루어지고 있다. 우리나라에서도 IT 기술의 발달과 함께 무인시스템에 관한 연구가 활발히 진행되고 있지만 아직 개발 실적은 미미한 수준이다. 이 연구에서는 바지(barge)선형의 초소형자율 무인선박(USV)을 개발하고자 하였다. 자율항법 알고리즘 개발에 GPS센서의 위치 정보를 기반으로 대권항법 계산식을 적용하였으며, 프로그래밍은 NI사의 LabVIEW 8.2를 이용하였다. 조타제어는 펄스진폭변조 방식으로 하였다. 또한, 엔진시스템은 전동모터 및 전자 변속기로 구성하였고, 엔진시스템 냉각방식으로 DC모터펌프를 이용한 해수 직접냉각방식을 채용하였다. 무인선박을 자체 설계 제작하고, 해상실험을 통해 자율운항 알고리즘의 유효성을 검증하였다.

This paper presents a goal-directed reactive obstacle avoidance method based on lane method. The reactive collision avoidance is necessarily required for a robot to navigate autonomously in dynamic environments. Many methods are suggested to implement this concept and one of them is the lane method. The lane method divides the environment into lanes and then chooses the best lane to follow. The proposed method does not use the discrete lane but chooses a line closest to the original target line without collision when an obstacle is detected, thus it has a merit in the aspect of running time and it is more proper for narrow corridor environment. If an obstacle disturbs the movement of a robot by blocking a target path, a robot generates a temporary target line, which is parallel to an original target line and tangential to an obstacle circle, to avoid a collision with an obstacle and changes to and follows that line until an obstacle is removed. After an obstacle is clear, a robot returns to an original target line and proceeds to the goal point. Obstacle is recognized by laser range finder sensor and represented by a circle. Our method has been implemented and tested in a corridor environment and experimental results show that our method can work reliably.

Recently, many vision-based navigation methods have been introduced as an intelligent robot application. However, many of these methods mainly focus on finding an image in the database corresponding to a query image. Thus, if the environment changes, for example, objects moving in the environment, a robot is unlikely to find consistent corresponding points with one of the database images. To solve these problems, we propose a novel navigation strategy which uses fast motion estimation and a practical scene recognition scheme preparing the kidnapping problem, which is defined as the problem of re-localizing a mobile robot after it is undergone an unknown motion or visual occlusion. This algorithm is based on motion estimation by a camera to plan the next movement of a robot and an efficient outlier rejection algorithm for scene recognition. Experimental results demonstrate the capability of the vision-based autonomous navigation against dynamic environments.

We propose a novel real-time obstacle avoidance method for rescue robots. This method, named the ELA(Emergency Level Around), permits the detection of unknown obstacles and avoids collisions while simultaneously steering the mobile robot toward safe position. In the ELA, we consider two sensor modules, PSD(Position Sensitive Detector) infrared sensors taking charge of obstacle detection in short distance and LMS(Laser Measurement System) in long distance respectively. Hence if a robot recognizes an obstacle ahead by PSD infrared sensors first, and judges impossibility to overcome the obstacle based on driving mode decision process, the order of priority is transferred to LMS which collects data of radial distance centered on the robot to avoid the confronted obstacle. After gathering radial information, the ELA algorithm estimates emergency level around a robot and generates a polar histogram based on the emergency level to judge where the optimal free space is. Finally, steering angle is determined to guarantee rotation to randomly direction as well as robot width for safe avoidance. Simulation results from wandering in closed local area which includes various obstacles and different conditions demonstrate the power of the ELA.

In this paper, a tracking algorithm for autonomous navigation of automated guided vehicles (AGVs) operating in container terminals is presented. The developed navigation algorithm takes the form of a federated information filter used to detect other AGVs and avoid obstacles using fused information from multiple sensors. Being equivalent to the Kalman filter (KF) algebraically, the information filter is extended to N-sensor distributed dynamic systems. In multi-sensor environments, the information-based filter is easier to decentralize, initialize, and fuse than a KF-based filter. It is proved that the information state and the information matrix of the suggested filter, which are weighted in terms of an information sharing factor, are equal to those of a centralized information filter under the regular conditions. Numerical examples using Monte Carlo simulation are provided to compare the centralized information filter and the proposed one.