김아영 교수

The high diversity of urban environments, at both the inter and intra levels, poses challenges for robotics research. Such challenges include discrepancies in urban features between cities and the deterioration of sensor measurements within a city. With such diversity in consideration, this paper aims to provide Light Detection and Ranging (LiDAR) and image data acquired in complex urban environments. In contrast to existing datasets, the presented dataset encapsulates various complex urban feat

This paper reports a real-time monocular visual simultaneous localization and mapping (SLAM) algorithm and results for its application in the area of autonomous underwater ship hull inspection. The proposed algorithm overcomes some of the specific challenges associated with underwater visual SLAM, namely, limited field of view imagery and feature-poor regions. It does so by exploiting our SLAM navigation prior within the image registration pipeline and by being selective about which imagery is c

This paper reports on an integrated navigation algorithm for the visual simultaneous localization and mapping (SLAM) robotic area coverage problem. In the robotic area coverage problem, the goal is to explore and map a given target area within a reasonable amount of time. This goal necessitates the use of minimally redundant overlap trajectories for coverage efficiency; however, visual SLAM’s navigation estimate will inevitably drift over time in the absence of loop closures. Therefore, efficien

Abstract Odometry is crucial for robot navigation, particularly in situations where global positioning methods like global positioning system are unavailable. The main goal of odometry is to predict the robot’s motion and accurately determine its current location. Various sensors, such as wheel encoder, inertial measurement unit (IMU), camera, radar, and Light Detection and Ranging (LiDAR), are used for odometry in robotics. LiDAR, in particular, has gained attention for its ability to provide r

This paper reports the application of vision based simultaneous localization and mapping (SLAM) to the problem of autonomous ship hull inspection by an underwater vehicle. The goal of this work is to automatically map and navigate the underwater surface area of a ship hull for foreign object detection and maintenance inspection tasks. For this purpose we employ a pose-graph SLAM algorithm using an extended information filter for inference. For perception, we use a calibrated monocular camera sys

This paper reports on an integrated navigation algorithm for the visual simultaneous localization and mapping (SLAM) robotic area coverage problem. In the robotic area coverage problem, the goal is to explore and map a given target area in a reasonable amount of time. This goal necessitates the use of minimally redundant overlap trajectories for coverage efficiency; however, visual SLAM's navigation estimate will inevitably drift over time in the absence of loop-closures. Therefore, efficient ar

This paper reports on a system for an autonomous underwater vehicle to perform in situ , multiple session hull inspection using long‐term simultaneous localization and mapping (SLAM). Our method assumes very little a priori knowledge, and it does not require the aid of acoustic beacons for navigation, which is a typical mode of navigation in this type of application. Our system combines recent techniques in underwater saliency‐informed visual SLAM and a method for representing the ship hull surf

Place recognition is crucial for robot localization and loop closure in simultaneous localization and mapping (SLAM). Light Detection and Ranging (LiDAR), known for its robust sensing capabilities and measurement consistency even in varying illumination conditions, has become pivotal in various fields, surpassing traditional imaging sensors in certain applications. Among various types of LiDAR, spinning LiDARs are widely used, while non-repetitive scanning patterns have recently been utilized in

This paper presents accurate urban map generation using digital map-based Simultaneous Localization and Mapping (SLAM). Throughout this work, our main objective is generating a 3D and lane map aiming for sub-meter accuracy. In conventional mapping approaches, achieving extremely high accuracy was performed by either (i) exploiting costly airborne sensors or (ii) surveying with a static mapping system in a stationary platform. Mobile scanning systems recently have gathered popularity but are most

Compared to the flourishing researches on terrestrial optical images, deep learning in underwater imaging has not been highlighted. Although some approaches applied deep learning in their underwater imaging still no major application has been found in underwater sonar imaging. Notably, the fundamental limitation in underwater image data would be the main cause of the bottleneck. To alleviate this issue, this paper introduces a simulation-generated dataset for object detection in underwater sonar

Abstract This paper presents a real‐time and channel‐invariant visibility enhancement algorithm using a hybrid image enhancement approach. The proposed method is initially motivated by an underwater visual simultaneous localization and mapping (SLAM) failure in a turbid medium. The environments studied contain various particles and are dominated by a different image degradation model. Targeting image enhancement for degraded images but not being limited to it, the proposed method provides a high

This paper presents an approach for making a dataset using a 3D CAD model for deep learning based underwater object detection and pose estimation. We also introduce a simple pose estimation network for underwater objects. In the experiment, we show that object detection and pose estimation networks trained via our synthetic dataset present a preliminary potential for deep learning based approaches in underwater. Lastly, we show that our synthetic image dataset provides meaningful performance for

본 연구의 목적은 규모의 경제와 집적 경제가 제조업의 생산성에 미치는 영향을 분석하는 것이다. 집적변수를 고려한 초월대수 비용함수의 추정을 통해 수도권 및 인접지역의 제조업 생산성을 비용 절감 측면에서 분석한 결과, 과밀억제권역은 1996년 이후 제조업의 규모 불경제가 발생하였으며, 도시화 경제는 존재하지만 그 크기는 점차 줄어들고 있는 것으로 나타났다. 반대로 성장관리권역의 경우 규모의 경제뿐만 아니라 도시화 경제가 유지되고 있는 것으로 평가되었다. 따라서 일괄적인 수도권 집중 억제정책의 적용보다는 공간에 따라 차별화된 정책이 필요하다. 또한 과밀억제권역에서 수도권 인접지역으로의 인구 및 제조업의 이동은 두 지역의 생산성 향상을 가져올 것으로 예상된다.