High-precision maps are widely applied in intelligent-driving vehicles for localization and planning tasks. The vision sensor, especially monocular cameras, has become favoured in mapping approaches due to its high flexibility and low cost. However,...
Perception of road structures especially the traffic intersections by visual sensors is an essential task for automated driving. However, compared with intersection detection or visual place recognition, intersection re-identification (intersection r...
This paper proposes an adaptive absolute ego-motion estimation method using wearable visual-inertial sensors for indoor positioning. We introduce a wearable visual-inertial device to estimate not only the camera ego-motion, but also the 3D motion of...
Simultaneous Localization and Mapping (SLAM) has always been the focus of the robot navigation for many decades and becomes a research hotspot in recent years. Because a SLAM system based on vision sensor is vulnerable to environment illumination and...
This paper presents a comprehensive survey of deep learning-based methods for 3D object detection in autonomous driving, focusing on their use of diverse sensor modalities, including monocular cameras, stereo vision, LiDAR, radar, and multi-modal fus...
A growing need for sampling environmental spaces in high detail is driving the rapid development of non-destructive three-dimensional (3D) sensing technologies. LiDAR sensors, capable of precise 3D measurement at various scales from indoor to landsca...
Fixed roadside monocular cameras are widely used as low-cost sensing devices in intelligent transportation systems; however, extracting reliable three-dimensional (3D) information from such sensors remains challenging due to limited baselines, long o...
This paper presents a sensor fusion strategy applied for Simultaneous Localization and Mapping (SLAM) in dynamic environments. The designed approach consists of two features: (i) the first one is a fusion module which synthesizes line segments obtain...
We propose a completely unsupervised approach to simultaneously estimate scene depth, ego-pose, ground segmentation and ground normal vector from only monocular RGB video sequences. In our approach, estimation for different scene structures can mutua...
Deep learning is the mainstream paradigm in computer vision and machine learning, but performance is usually not as good as expected when used for applications in robot vision. The problem is that robot sensing is inherently active, and often, releva...
In this paper, an onboard vision-based system for the autonomous landing of a low-cost quadrotor is presented. A novel landing pad with different optical markers sizes is carefully designed to be robustly recognized at different distances. To provide...
This paper presents the design of a low-cost, compact instrumentation system to enable six degree of freedom motion tracking of acetal bricks within an experimental model of a cracked Advanced Gas-Cooled Reactor (AGR) core. The system comprises optic...
With the development of simultaneous positioning and mapping technology in the field of automatic driving, the current simultaneous localization and mapping scheme is no longer limited to a single sensor and is developing in the direction of multi-se...
This paper presents an approach to analyse the quality, in terms of precision and reliability, of a system which integrates—at the observation-level—landmark positions and GNSS measurements, obtained with a single camera and a digital map...
Aiming at the problem of blind field of view caused by the change in the vehicle’s yaw angle when the self-driving vehicle is turning or changing lanes, this paper proposes a camera rotation strategy based on monocular active environment sensin...
Estimating the absolute scale of reconstructed camera trajectories in monocular odometry is a challenging task due to the inherent scale ambiguity in any monocular vision system. One promising solution is to fuse data from different sensors, which ca...
This article presents a new sensor fusion method for visual simultaneous localization and mapping (SLAM) through integration of a monocular camera and a 1D-laser range finder. Such as a fusion method provides the scale estimation and drift correction...
Simultaneous localization and mapping (SLAM) is an important problem to solve in robotics theory in order to build truly autonomous mobile robots. This work presents a novel method for implementing a SLAM system based on a single camera sensor. The S...
Cameras are sensors that are available anywhere and to everyone, and can be placed easily inside vehicles. While stereovision setups of two or more synchronized cameras have the advantage of directly extracting 3D information, a single camera can be...
A new approach to the monocular simultaneous localization and mapping (SLAM) problem is presented in this work. Data obtained from additional bearing-only sensors deployed as wearable devices is fully fused into an Extended Kalman Filter (EKF). The w...
Monocular vision is one of the most commonly used noncontact six-degrees-of-freedom (6-DOF) pose estimation methods. However, the large translational DOF measurement error along the optical axis of the camera is one of its main weaknesses, which grea...
To address the limitations of single-sensor systems in environmental perception, such as the difficulty in comprehensively capturing complex environmental information and insufficient detection accuracy and robustness in dynamic environments, this st...
Low-cost Global Navigation Satellite System (GNSS) receivers and monocular cameras are widely used in daily activities. The complementary nature of these two devices is ideal for outdoor navigation. In this paper, we investigate the integration of GN...
With the growth of global liquefied natural gas (LNG) demand, automation technology has become a key trend to improve the efficiency and safety of LNG handling. In this study, a novel automatic docking system is proposed which adopts a staged docking...
Aqua farms will be the most frequently encountered obstacle when autonomous ships sail along the coastal area of Korea. We used YOLOv5 to create a model that detects aquaculture buoys. The distances between the buoys and the camera were calculated ba...
Most of the humanoid social robots currently diffused are designed only for verbal and animated interactions with users, and despite being equipped with two upper arms for interactive animation, they lack object manipulation capabilities. In this pap...
This work presents a variant approach to the monocular SLAM problem focused in exploiting the advantages of a human-robot interaction (HRI) framework. Based upon the delayed inverse-depth feature initialization SLAM (DI-D SLAM), a known monocular tec...
Owing to recent advancements in deep learning methods and relevant databases, it is becoming increasingly easier to recognize 3D objects using only RGB images from single viewpoints. This study investigates the major breakthroughs and current progres...
Simultaneous localization and mapping (SLAM) is emerging as a prominent issue in computer vision and next-generation core technology for robots, autonomous navigation and augmented reality. In augmented reality applications, fast camera pose estimati...
Monocular cameras and multibeam imaging sonars are common sensors of Unmanned Underwater Vehicles (UUV). In this paper, we propose a new method for calibrating a hybrid sonar–vision system. This method is based on motion comparisons between bot...
Precise navigation is often performed by sensor fusion of different sensors. Among these sensors, optical sensors use image features to obtain the position and attitude of the camera. Runway relative navigation during final approach is a special case...
Many current and future applications of underwater robotics require real-time sensing and interpretation of the environment. As the vast majority of robots are equipped with cameras, computer vision is playing an increasingly important role it this f...
Monocular 3D object detection refers to detecting 3D objects using a single camera. This approach offers low sensor costs, high resolution, and rich texture information, making it widely adopted. However, monocular sensors face challenges from enviro...
In recent years, multi-sensor fusion technology has made enormous progress in 3D reconstruction, surveying and mapping, autonomous driving, and other related fields, and extrinsic calibration is a necessary condition for multi-sensor fusion applicati...
This paper introduces a cost-effective autonomous charging docking system that utilizes a monocular camera and ArUco markers. Traditional monocular vision-based approaches, such as SolvePnP, are sensitive to viewing angles, lighting conditions, and c...
Accurate and reliable tracking of multi-pedestrian is of great importance for autonomous driving, human-robot interaction and video surveillance. Since different scenarios have different best-performing sensors, sensor fusion perception plans are bel...
In recent years, there has been extensive research and application of unsupervised monocular depth estimation methods for intelligent vehicles. However, a major limitation of most existing approaches is their inability to predict absolute depth value...
The present paper describes a vision-based simultaneous localization and mapping system to be applied to Unmanned Aerial Vehicles (UAVs). The main contribution of this work is to propose a novel estimator relying on an Extended Kalman Filter. The est...
Sign language recognition is essential in hearing-impaired people’s communication. Wearable data gloves and computer vision are partially complementary solutions. However, sign language recognition using a general monocular camera suffers from...
Autonomous technologies have revolutionized transportation, military operations, and space exploration, necessitating precise localization in environments where traditional GPS-based systems are unreliable or unavailable. While widespread for outdoor...
Gait analysis plays an important role in the fields of healthcare and sports sciences. Conventional gait analysis relies on costly equipment such as optical motion capture cameras and wearable sensors, some of which require trained assessors for data...
In the rapidly evolving field of computer vision and machine learning, 3D skeleton estimation is critical for applications such as motion analysis and human–computer interaction. While stereo cameras are commonly used to acquire 3D skeletal dat...
This research paper proposes a real-time obstacle avoidance strategy for mobile robots with a monocular camera. The approach uses a binary semantic segmentation FCN-VGG-16 to extract features from images captured by the monocular camera and estimate...
Camera-centric perception has matured into a cornerstone of modern autonomy, from self-driving cars and factory cobots to underwater and planetary exploration. This review synthesizes more than a decade of progress in vision-based robotic navigation...
In this paper an original, easy to reproduce, semi-analytic calibration approach is developed for hardware-in-the-loop performance assessment of pose determination algorithms processing point cloud data, collected by imaging a non-cooperative target...
Recently, visual odometry and SLAM (Simultaneous Localization and Mapping) have shown tremendous performance improvements compared to LiDAR and 3D sensor techniques. Unfortunately, attempts to achieve these improvements always face numerous challenge...
In recent years, self-supervised monocular depth estimation has gained popularity among researchers because it uses only a single camera at a much lower cost than the direct use of laser sensors to acquire depth. Although monocular self-supervised me...
In this paper, we propose an underwater object detection method using monocular vision sensors. In addition to commonly used visual features such as color and intensity, we investigate the potential of underwater object detection using light transmis...
Accurate three-dimensional displacement measurements of bridges and other structures have received significant attention in recent years. The main challenges of such measurements include the cost and the need for a scalable array of instrumentation....
As autonomous driving is quickly becoming a reality, the most considerable challenge with self-driving remains safety, as the car must process surroundings to make the correct predictions. This paper explores the detection and classification of movin...
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