In the process of controlling an unmanned vehicle, it is practically important that under conditions of rapidly changing dynamic constraints, control laws be developed that would be optimal with respect to a given quality functional or a multicriteri...
Indoor location estimation is crucial to provide context-based assistance in home environments. In this study, a method for simultaneous indoor pedestrian localization and house mapping is proposed and evaluated. The method fuses a person’s mov...
Research and development of autonomous mobile robotic solutions that can perform several active agricultural tasks (pruning, harvesting, mowing) have been growing. Robots are now used for a variety of tasks such as planting, harvesting, environmental...
Navigation technology is one of the most important challenges in the applications of autonomous underwater vehicles (AUVs) which navigate in the complex undersea environment. The ability of localizing a robot and accurately mapping its surroundings s...
Indoor localization and human activity recognition are two important sources of information to provide context-based assistance. This information is relevant in ambient assisted living (AAL) scenarios, where older adults usually need supervision and...
Simultaneous localization and mapping (SLAM) is an active localization method for Autonomous Underwater Vehicle (AUV), and it can mainly be used in unknown and complex areas such as coastal water, harbors, and wharfs. This paper presents a practical...
This study proposes a solution for Active Simultaneous Localization and Mapping (Active SLAM) of robots in unknown indoor environments using a combination of Deep Deterministic Policy Gradient (DDPG) path planning and the Cartographer algorithm. To e...
Many applications require the localization of a moving object, e.g., a robot, using sensory data acquired from embedded devices. Simultaneous localization and mapping from vision performs both the spatial and temporal fusion of these data on a map wh...
Recent advancements in simultaneous localization and mapping (SLAM) have significantly improved the handling of dynamic objects. Traditionally, SLAM systems mitigate the impact of dynamic objects by extracting, matching, and tracking features. Howeve...
Three dimensional (3D) imaging technology has been widely used for many applications, such as human–computer interactions, making industrial measurements, and dealing with cultural relics. However, existing active methods often require both lar...
The autonomous movement of the mobile robotic system is a complex problem. If there are dynamic objects in the space when performing this task, the complexity of the solution increases. To avoid collisions, it is necessary to implement a suitable det...
Aiming at the problems of complex texture, variable interference factors and large sample acquisition in surface defect detection, a generic method of automated surface defect detection based on a bilinear model was proposed. To realize the automatic...
The ability to estimate the current locations of mobile robots that move in a limited workspace and perform tasks is fundamental in robotic services. However, even if the robot is given a map of the workspace, it is not easy to quickly and accurately...
The current optimization approaches of construction machinery are mainly based on internal sensors. However, the decision of a reasonable strategy is not only determined by its intrinsic signals, but also very strongly by environmental information, e...
Face alignment methods have been actively studied using coordinate and heatmap regression tasks. Although these regression tasks have the same objective for facial landmark detection, each task requires different valid feature maps. Therefore, it is...
Multi-robot systems (MRSs) offer distinct advantages in large-scale exploration but require tight coupling between decentralized decision-making and collaborative estimation. This survey reviews learning-based multi-robot Active Collaborative Simulta...
When performing indoor tasks, miniature swarm robots are suffered from their small size, poor on-board computing power, and electromagnetic shielding of buildings, which means that some traditional localization methods, such as global positioning sys...
This paper addresses an autonomous navigation method for the autonomous underwater vehicle (AUV) C-Ranger applying information-filter-based simultaneous localization and mapping (SLAM), and its sea trial experiments in Tuandao Bay (Shangdong Province...
At present, pedestrian navigation systems using smartphones have become common in daily activities. For their ubiquitous, accurate, and reliable services, map information collection is essential for constructing comprehensive spatial databases. Previ...
The insurgence of superresolution microscopy into the fields of virology and microbiology has begun to enable the mapping of molecular assemblies critical for host–pathogen interfaces that organize on a scale below the resolution limit of the light m...
Coupled simultaneous localization and mapping (SLAM) and multi-object tracking have been studied in recent years. Although these tasks achieve promising results, they mainly associate keypoints and objects across frames separately, which limits their...
Future planetary exploration missions will rely heavily on efficient human–robot interaction to ensure astronaut safety and maximize scientific return. In this context, digital twins offer a promising tool for planning, simulating, and optimizi...
Simultaneous localization and mapping (SLAM) is fundamental for intelligent mobile units to perform diverse tasks. Recent work has shown that integrating neural rendering and SLAM showed promising results in photorealistic environment reconstruction....
Cross-domain ground-based cloud classification is a challenging issue as the appearance of cloud images from different cloud databases possesses extreme variations. Two fundamental problems which are essential for cross-domain ground-based cloud clas...
Finding depth information with stereo matching using a deep learning algorithm for embedded systems has recently gained significant attention owing to emerging high-performance mobile graphics processing units (GPUs). Several researchers have propose...
Loop Closure (LC) is a crucial task in Simultaneous Localization and Mapping (SLAM) for Autonomous Ground Vehicles (AGV). It is an active research area because it improves global localization efficiency. The consistency of the global map and the accu...
This article presents a comprehensive review of the Active Simultaneous Localization and Mapping (A-SLAM) research conducted over the past decade. It explores the formulation, applications, and methodologies employed in A-SLAM, particularly in trajec...
Simultaneous Localization and Mapping (SLAM) is an active area of robot research. SLAM with a laser range finder (LRF) is effective for localization and navigation. However, commercial robots usually have to use low-cost LRF sensors, which result in...
Traditional urban analysis and planning often neglect intangible emotional responses, leaving a gap in comprehending and addressing appropriately how urban spaces are experienced by individuals and communities. However, in contemporary urban research...
High-resolution (HR) mapping of the gastrointestinal (GI) bioelectrical activity is an emerging method to define the GI dysrhythmias such as gastroparesis and functional dyspepsia. Currently, there is no solution available to conduct HR mapping in lo...
As an important part of video understanding, temporal action detection (TAD) has wide application scenarios. It aims to simultaneously predict the boundary position and class label of every action instance in an untrimmed video. Most of the existing...
People with disabilities (PWD) face a number of challenges such as obstacle avoidance or taking a minimum path to reach a destination while travelling or taking public transport, especially in airports or bus stations. In some cases, PWD, and specifi...
Transcranial magnetic stimulation (TMS) activates brain cells in a noninvasive manner and can be used for mapping brain motor functions. However, the complexity of the brain anatomy prevents the determination of the exact location of the stimulated s...
Wideband interference (WBI) can significantly reduce the image quality and interpretation accuracy of synthetic aperture radar (SAR). To eliminate the negative effects of WBI on SAR, we propose a novel end-to-end data-driven approach to mitigate WBI....
Accurate diagnosis of myocardial infarction (MI) holds significant clinical importance for public health systems. Deep learning-based ECG, classification and localization methods can automatically extract features, thereby overcoming the dependence o...
The application of intravehicular robotic assistants (IRA) can save valuable working hours for astronauts in space stations. There are various types of IRA, such as an accompanying drone working in microgravity and a dexterous humanoid robot for coll...
In response to the current situation of backward automation levels, heavy labor intensities, and high accident rates in the underground coal mine auxiliary transportation system, the mining trackless auxiliary transportation robot (MTATBOT) is presen...
This paper proposes an iterative learning framework for a class of fractional-order nonlinear multi-agent systems operating under directed iteration-varying switching topologies. To suppress trial-to-trial fluctuations in initial states, a P-type ini...
The hardware architecture of a deep-neural-network-based feature point extraction method is proposed for the simultaneous localization and mapping (SLAM) in robotic applications, which is named the Feature Point based SLAM Network (FPSNET). Some key...
Background: Phase analysis has been used to identify and localize atrial fibrillation (AF) sources for targeted ablation. We previously demonstrated that repetitive wannabe reentry (incomplete reentry) often generated an apparent stable rotor using p...
The simultaneous localization and mapping (SLAM) technique provides long-term near-seafloor navigation for autonomous underwater vehicles (AUVs). However, the stability of the interest point detector (IPD) remains challenging in the seafloor environm...
Visual inertial odometry (VIO) is the front-end of visual simultaneous localization and mapping (vSLAM) methods and has been actively studied in recent years. In this context, a time-of-flight (ToF) camera, with its high accuracy of depth measurement...
Volcanic eruptions pose a major natural hazard influencing the environment, climate and human beings at different temporal and spatial scales. Nevertheless, several volcanoes worldwide are poorly monitored and assessing the impact of their eruptions...
Uncertainty remains a central challenge in robotic navigation, exploration, and coordination. This paper examines how Partially Observable Markov Decision Processes (POMDPs) and their decentralized variants (Dec-POMDPs) provide a rigorous foundation...
The manuscript intends to describe different methodologies for the acquisition, data processing, and identification of strategies aimed at improving the quality of 3D point cloud production using latest-generation sensors in the field of cultural her...
With the progressively deteriorating global ecological environment and the gradual escalation of human activities, the survival of wildlife has been severely impacted. Hence, a rapid, precise, and reliable method for detecting wildlife holds immense...
Over the last decade, dual active bridge (DAB) converters have become critical components in high-frequency power conversion systems. Recently, intensive efforts have been directed at optimizing DAB converter design and control. In particular, severa...
Airborne magnetic particles (AMPs) are associated with potentially toxic elements, and their size, mineralogy, and concentration can significantly impact both the environment and human health. However, their spatial analysis is often limited by small...
For more than a decade, both academia and industry have focused attention on the computer vision and in particular the computational color constancy (CVCC). The CVCC is used as a fundamental preprocessing task in a wide range of computer vision appli...
LiDAR (light detection and ranging), as an active sensor, is investigated in the simultaneous localization and mapping (SLAM) system. Typically, a LiDAR SLAM system consists of front-end odometry and back-end optimization modules. Loop closure detect...
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