Seonghun Hong

A robust loop-closure method for visual SLAM in unstructured seafloor environments

This paper addresses the problem of visual simultaneous localization and mapping (SLAM) in an unstructured seabed environment that can be applied to an unmanned underwater vehicle equipped with a single monocular camera as the main measurement sensor. Monocular vision is regarded as an efficient sensing option in the context of SLAM, however it poses a variety of challenges when the relative motion is determined by matching a pair of images in the case of in-water visual SLAM. Among the various challenges, this research focuses on the problem of loop-closure which is one of the most important issues in SLAM. This study proposes a robust loop-closure algorithm in order to improve operational performance in terms of both navigation and mapping by efficiently reconstructing image matching constraints. To demonstrate and evaluate the effectiveness of the proposed loop-closure method, experimental datasets obtained in underwater environments are used, and the validity of the algorithm is confirmed by a series of comparative results.

Development of an Unmanned Surface Vehicle System for the 2014 Maritime RobotX Challenge

This paper addresses the development of an unmanned surface vehicle (USV) system by Team Angry-Nerds from KAIST for the inaugural Maritime RobotX Challenge competition, which was held on October 20-26, 2014, in Marina Bay, Singapore. The USV hardware was developed on a catamaran platform by integrating various system components, including propulsion, sensors, computer, power, and emergency systems. The competition comprised five mission tasks: 1) navigation and control, 2) underwater search and report, 3) automatic docking, 4) buoy search and observation, and 5) obstacle detection and avoidance. Onboard intelligence was a key factor for all of the mission tasks which needed to be performed autonomously with no human intervention. Software algorithms for vehicle autonomy were developed, and executable computer codes were implemented and integrated with the developed USV hardware system. This paper describes the development process of the USV system and its application to the competition mission tasks.

Online underwater optical mapping for trajectories with gaps

This paper proposes a vision-only online mosaicing method for underwater surveys. Our method tackles a common problem in low-cost imaging platforms, where complementary navigation sensors produce imprecise or even missing measurements. Under these circumstances, the success of the optical mapping depends on the continuity of the acquired video stream. However, this continuity cannot be always guaranteed due to the motion blurs or lack of texture, common in underwater scenarios. Such temporal gaps hinder the extraction of reliable motion estimates from visual odometry, and compromise the ability to infer the presence of loops for producing an adequate optical map. Unlike traditional underwater mosaicing methods, our proposal can handle camera trajectories with gaps between time-consecutive images. This is achieved by constructing minimum spanning tree which verifies whether the current topology is connected or not. To do so, we embed a trajectory estimate correction step based on graph theory algorithms. The proposed method was tested with several different underwater image sequences and results were presented to illustrate the performance.

Underwater pose estimation relative to planar hull surface using stereo vision

For creating a precise visual map by autonomous ship-hull inspection using an unmanned underwater vehicle, it is a crucial capability for the vehicle (or camera) to maintain a pose relative to the hull surface. In this study, a relative pose estimation algorithm is introduced using a stereo vision system. The proposed approach utilizes 3D point cloud data that can be generated by a sparse feature matching technique between a pair of stereo images. The relative pose information can be obtained by applying a surface normal estimation algorithm for the 3D points. Experimental results using underwater images is shown to verify the practical feasibility of the proposed approach.

Visual SLAM with keyframe selection for underwater structure inspection using an autonomous underwater vehicle

This study introduces an efficient visual simultaneous localization and mapping (SLAM) algorithm that can be applied to autonomous inspection of underwater structures, such as ship hulls, dams, and marine structures. Considering that visual features on the surface of typical underwater structures are not uniformly distributed, the proposed visual SLAM algorithm includes an intra-image analysis scheme that evaluates whether each image obtained from the surface is informative before extracting the features. By using only potentially effective images for feature-based image registration, the computational efficiency of the visual SLAM can be greatly improved, compared with the conventional exhaustive approach. Experimental results using a hover-capable unmanned underwater vehicle verify the practical feasibility and performance of the proposed methodology.

Efficient visual SLAM using selective image registration for autonomous inspection of underwater structures

Visual inspection of underwater structures including ship-hull inspection has been performed by human divers. It is a highly dangerous task and thus can be a potential application for unmanned underwater vehicles. This paper introduces an efficient visual simultaneous localization and mapping (SLAM) algorithm that can be applied to the autonomous inspection of underwater structures. Considering that visual features are sparsely located on the surface of typical underwater structures, the proposed visual SLAM algorithm employs a selective image registration scheme consisting of key-frame selection and key-pair selection. By using only potentially effective images and image pairs for feature-based image registration, the computational burden of the visual SLAM can be substantially reduced, compared with the conventional method. Experimental results using a hover-capable unmanned underwater vehicle verify the practical feasibility and performance of the proposed methodology.

Development of a Hover-capable AUV System for In-water Visual Inspection via Image Mosaicking

Recently, UUVs (unmanned underwater vehicles) have increasingly been applied in various science and engineering applications. In-water inspection, which used to be performed by human divers, is a potential application for UUVs. In particular, the operational safety and performance of in-water inspection missions can be greatly improved by using an underwater robotic vehicle. The capabilities of hovering maneuvers and automatic image mosaicking are essential for autonomous underwater visual inspection. This paper presents the development of a hover-capable autonomous underwater vehicle system for autonomous in-water inspection, which includes both a hardware platform and operational software algorithms. Some results from an experiment in a model basin are presented to demonstrate the feasibility of the developed system and algorithms. Received 9 November 2015, revised 13 May 2016, accepted 24 June 2016 Corresponding author Jinwhan Kim: +82-042-350-1519, jinwhan@kaist.ac.kr ◯c 2016, The Korean Society of Ocean Engineers It is noted that this paper is revised edition based on proceedings of KSOE 2015 in Daejeon. 1. 서 론 해양 플랜트, 댐, 선체 등과 같은 해양 구조물들의 관리 및 유 지보수를 위해서는 수중 육안 검사가 필요하다. 이러한 수중 검 사는 일반적으로 유인 잠수부에 의해 수행되는데, 고난이도 고 위험 작업의 특성상 비용 대비 효율이 크게 떨어지며 안정성의 문제로 충분하고 세밀한 검사가 어려워 검사 결과의 정확성과 신뢰도에 명확한 한계가 존재한다. 최근 해양 로봇공학 분야가 지속적으로 발전함에 따라 임무 특성에 맞는 여러 형태의 무인 수중 운동체들이 활용되고 있다. 특히 ROV(Remotely-operated vehicle)는 수중 검사 및 탐사를 수행하기 위해 가장 널리 활용되어 온 수중 운동체의 한 형태 이나, 지상의 조작 콘솔에 연결된 유선 작업의 특성상 그 운용 효율과 범위의 제약이 크다. 특히 제한된 시계 조건에서 ROV 가 운용될 경우, 전송되는 영상을 바탕으로 운용자의 시각에 전 적으로 의존해야 하므로 전반적인 작업 효율이 운용자의 숙련 도에 크게 좌우되며 시간에 따른 피로 증가로 집중도와 효율이 떨어지기 때문에 장시간 운용이 어렵다. 한편, 일반적인 어뢰형의 AUV(Autonomous underwater vehicle) 는 그 외형 상 저항 및 추진에 유리하고 에너지 효율이 높아 운 용 반경이 넓다는 장점이 있으나 운동성의 제약으로 제자리 유 영이나 임의 방향으로 자유로운 이동이 불가능하다. 이러한 이 유로, 해양 물리량 측정 등 단순한 운용 외에 복잡한 임무 수행 에는 적합하지 못하다. 본 연구에서는 기존의 유인 작업 또는 ROV를 사용한 수중 구조 물 검사 임무의 한계를 극복하고자 제한된 운동성을 갖는 기존의 어뢰형 AUV가 아닌 제자리에서 유영이 가능한 H-AUV (Hover-capable AUV) 시스템의 하드웨어 플랫폼 및 운용 알고리 즘의 개발을 목표로 한다. 2장에서는 H-AUV 플랫폼의 하드웨어 설계 및 구현에 대한 내용을 기술하고, 3장에서 카메라 영상 기반