김종휘 교수

Abstract This study addresses the development of algorithms for multiple target detection and tracking in the framework of sensor fusion and its application to autonomous navigation and collision avoidance systems for the unmanned surface vehicle (USV) Aragon. To provide autonomous navigation capabilities, various perception sensors such as radar, lidar, and cameras have been mounted on the USV platform and automatic ship detection algorithms are applied to the sensor measurements. The relative

This paper presents a multimodal maritime dataset and the data collection procedure used to gather it, which aims to facilitate autonomous navigation in restricted water environments. The dataset comprises measurements obtained using various perception and navigation sensors, including a stereo camera, an infrared camera, an omnidirectional camera, three LiDARs, a marine radar, a global positioning system, and an attitude heading reference system. The data were collected along a 7.5-km-long rout

Abstract In this paper, we present the development of autonomous navigation capabilities for small cruise boats, and their verification by field experiments in a canal and its surrounding waters. A cruise boat was converted to an autonomous surface vehicle (ASV) by installing various sensors and actuators to enable autonomous navigation. Navigation and perception sensors, such as global positioning system, attitude and heading reference system, radar, light detection and ranging (LiDAR), and cam

This letter presents an integrated navigation and control strategy for an autonomous surface vehicle (ASV) to operate in narrow waterways without relying on GPS. The proposed method uses a camera and a light detection and ranging (LiDAR) sensor to detect navigable regions in the waterway. A deep learning-based semantic segmentation algorithm is applied to detect the navigable region in camera images, and the segmented region is projected onto the water surface using planar homography. A line-det

This paper addresses the autonomous landing of an unmanned aerial vehicle (UAV) on a ground vehicle. Unlike most of the previous research on autonomous UAV landing that used onboard sensors mounted on the UAV, this study suggests using a lidar mounted on a ground vehicle for lidar-guided landing. To estimate the relative position of the UAV with respect to the landing platform, a clustering algorithm is applied. In addition, to enhance the safety of landing, a decision making procedure based on

This paper addresses a vehicle localization method that fuses aerial maps and lidar data in urban canyon environments where global positioning system (GPS) signals are inaccurate. The boundaries of buildings are extracted from the aerial map and they are matched to point cloud data provided by the lidar. However, most aerial maps contain perspective projection distortions which can be significant in urban canyons with tall buildings. In this study, a new method to correct such projection distort

Recently, autonomous surface vehicles (ASVs) have attracted much research attention because of their potential effectiveness in carrying out various maritime missions such as surveillance and environmental monitoring. Situation awareness is a critical ability, and the camera is an essential sensor for ASVs in conducting such missions by automatically detecting and tracking objects in the surrounding environment. We detect and track the objects robustly by extracting the detection uncertainty and

This study presents a collision avoidance algorithm that considers the international regulations for preventing collisions at sea for narrow channels. The collision avoidance process for narrow channels may vary depending on the shape of the channel; therefore, implementing such an algorithm for autonomous navigation is not straightforward. In this study, curvilinear coordinates are introduced to represent the channel’s geometric shape using a parametric curve, B-spline. In addition, traffic rul

We discuss GPS-free localization in urban areas using a lidar and a 2D online map with building outlines. To achieve this, the boundaries of buildings extracted from the reference map are matched to 3D point cloud data provided by the lidar. The normalized mutual information between them is maximized. The matching result is used as a measurement and combined with odometry and inertial sensor measurements using an extended Kalman filter. The proposed method has been implemented and verified throu

Recent advancements in artificial intelligence and sensor technology have promoted increasing interest in maritime autonomous ships. In this paper, we present an overview of the perception and sensing technologies applied in autonomous ship research. We introduce various datasets collected using perception sensors, such as a camera, LiDAR, and marine radar. Object detection and semantic segmentation methods for detecting floating objects and navigable regions using individual sensors are present

The international regulations for preventing collisions at sea (COLREGs) are the rules of the road for marine surface vessels. However, certain ships fail to comply with COLREGs and their non-compliance poses a greater danger to the maritime safety. This study proposes a probabilistic model for intent inference of ship maneuvers which consist of an intent model, a dynamics model, and a measurement model. An algorithm based on the proposed graphical model is implemented to infer and predict the s