Navigation Aids Research Articles

Floor Plan Based Active Global Localization and Navigation Aid for Persons With Blindness and Low Vision

Floor Plan Based Active Global Localization and Navigation Aid for Persons With Blindness and Low Vision

A Review of CNN-Based Object Recognition and Tracking Systems for Visually Impaired People

Visually impaired persons (VIPs) face significant challenges in navigating their environments, impacting their independence and quality of life. This paper reviews recent advancements in assistive technologies aimed at enhancing mobility and safety for VIPs. It explores various systems, including wearable devices, object detection technologies, and navigation aids, highlighting their functionalities, limitations, and potential future develop- ment. The integration of machine learning and sensor technologies has led to innovative solutions that provide realtime feedback and improved spatial awareness for users. VIPsneed assistance in performing daily tasks such as object detection, obstacle recognition,and navigation, particularly in indoor and outdoor environments. The paper emphasizes the importance of protecting and ensuring the safety of VIPs. Devices typically use sensors like infrared, ultrasonic, and imagery to gather environmental data, which is then processed by machine learning techniques. Users receive feedback via auditory or vibratory means. The paper provides a comprehensive comparative analysis of assistive devices, discussing their key attributes, challenges, and limitations, along with a score-based evaluation to help select appropriate devices for specific needs

Polarization-selective metamaterial absorber using tailored Y-shaped SRR for UWB device and Doppler navigation aids applications

In this paper, we present an unprecedented metamaterial absorber design exhibiting exceptional characteristics in electromagnetic wave absorption. The proposed bent Y-shaped structure, fabricated on an FR-4 substrate with copper patches, showcases remarkable performance across a diverse frequency spectrum. Through exhaustive simulations in CST, this design manifests eight distinct resonant frequencies, achieving absorption rates exceeding 90 % at each resonance. The resonances, strategically spanning from L-band (3.728 GHz) through S-band, C-band, X-band, Ku-band, and K-band up to 22.664 GHz, signify unparalleled versatility and efficacy in mitigating electromagnetic radiation. It investigates the equivalent circuit parameters of a proposed metamaterial absorber design, focusing on inductance (L), capacitance (C), and resistance (R). This paper investigates the applications of UWB devices at 3.728 GHz and Doppler navigation aids at the 13.4 GHz frequency as regulated by the Federal Communications Commission. It includes a discussion on near-zero refractive Index Metamaterials (NZRIM), highlighting their potential utilization in achieving extraordinary control over wave behaviour. Notably, the absorber's inherent polarization insensitivity fortifies its adaptability in various applications. Additionally, the metamaterial exhibits near-zero or negative permittivity, altering electric response, while simultaneously demonstrating permeability absolute zero throughout all frequency bands sparking new avenues for exploration and challenging conventional electromagnetic theories.

Decoding the Impact of AI on Microsurgery: Systematic Review and Classification of Six Subdomains for Future Development.

The advent of artificial intelligence (AI) in microsurgery has tremendous potential in plastic and reconstructive surgery, with possibilities to elevate surgical precision, planning, and patient outcomes. This systematic review seeks to summarize available studies on the implementation of AI in microsurgery and classify these into subdomains where AI can revolutionize our field. Adhering to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a meticulous search strategy was used across multiple databases. The inclusion criteria encompassed articles that explicitly discussed AI's integration in microsurgical practices. Our aim was to analyze and classify these studies across subdomains for future development. The search yielded 2377 articles, with 571 abstracts eligible for screening. After shortlisting and reviewing 86 full-text articles, 29 studies met inclusion criteria. Detailed analysis led to the classification of 6 subdomains within AI applications in microsurgery, including information and knowledge delivery, microsurgical skills training, preoperative planning, intraoperative navigational aids and automated surgical tool control, flap monitoring, and postoperative predictive analytics for patient outcomes. Each subtheme showcased the multifaceted impact of AI on enhancing microsurgical procedures, from preoperative planning to postoperative recovery. The integration of AI into microsurgery signals a new dawn of surgical innovation, albeit with the caution warranted by its nascent stage and application diversity. The authors present a systematic review and 6 clear subdomains across which AI will likely play a role within microsurgery. Continuous research, ethical diligence, and cross-disciplinary cooperation is necessary for its successful integration within our specialty.

A Vibrotactile Belt for Measuring Vibrotactile Acuities on the Human Torso Using Coin Motors.

Accurate measurement of the vibrotactile acuities of the human torso is the key to designing effective torso-worn vibrotactile displays for healthcare applications such as navigation aids for visually impaired persons. Although efforts have been made to measure vibrotactile acuities, there remains a lack of systematic studies addressing the spatial, temporal, and intensity-related aspects of vibrotactile sensitivity on the human torso. In this work, a torso-worn vibrotactile belt consisting of two crossed coin motor arrays was designed and a psychophysical study was carried out to measure the spatial, temporal, and intensity-related vibrotactile acuities of a set of human subjects wearing the designed belt. The objective parameters of vibrational intensity and the timing latency of the coin motor were also determined before measuring the vibrotactile acuities. The experimental results indicated that the tested coin motor was able to generate a median number of five and six available just-noticeable differences in intensity and duration, respectively. Among the four parameters of vibrational intensity, the perceived intensity was the most relevant to vibrational displacement. The spatial acuities measured as the degree of two-point spatial thresholds (TPTs) showed less individual difference than the distance TPTs. The results from the current work provide valuable guidance for the design of a comfortable torso-worn vibrotactile display using coin motors.

Exploring Built Environment Visual Interactions: A SoftBIM Data-Driven Approach for a Database About the Outdoor View

Windows and glazed facades provide outdoor views, serving as vital sources of visual information that aid navigation and interaction within buildings. These views can trigger psychological and physiological responses, affecting individual well-being. However, optimizing outdoor view quality is challenging due to the complex interplay of factors influencing the building’s experience of vision. Managing the complexity of optimizing outdoor view quality within current digital frameworks for building design presents significant challenges. A key issue lies in the ambiguity of certain visual metrics, which are often difficult to translate into explicit descriptors of spatial configurations. Even when such metrics are available, their practical use as guiding tools in the design process is frequently obstructed by complex data interoperability procedures. These procedures are necessary to enable seamless data transfer across the multiple software environments involved in the design process. This study advocates for the softBIM paradigm, which optimizes workflows by embedding visual analysis results into target geometries. Supported by this process, the calculation of a metric to measure the impact of existing and planned visual obstructions on the vision of the targeted landmarks is proposed and analysed. This metric is specifically applied to assess the visual information incoming to the vertical facades of building envelopes, a context of application that denotes criteria of assessment different from the ones usually applied in the most established frameworks for visual analysis (e.g., isovist analysis). SoftBIM enables effective automation strategies to aid the metric computation and the processing of the results to implement seamless export and data implementation. The visual metric is built upon implementing the Ladybug suite and addresses the different limitations in the target-based visibility calculation supported by the tool.

Traffic advisory for ship encounter situation based on linear dynamic system

Enhancing Situation Awareness (SA) is crucial for maritime traffic safety. Various indicators have been developed to assess risks in encounter situations and support the SA of Vessel Traffic Service Operators (VTSOs) and Officers on Watch (OOW), including collision risk and traffic complexity. Despite the widespread use of these navigational aids, ship collision incidents have not been effectively reduced. This paper abstracts ship encounter situations as linear dynamic systems to enhance the understanding of traffic situations. A traffic advisory framework based on the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs) is proposed by integrating complexity metrics with risk indicators. The proposed method is validated through simulations of head-on, overtaking, and crossing scenarios, demonstrating its ability to accurately assess encounter complexity and issue advisories for free navigation, complexity, and resolution. Finally, we discuss the practical application of the proposed method through real-world experiments conducted in the waters of Qiongzhou Strait. The results indicate that the proposed method effectively quantifies the complexity of ship encounter situations and identifies high-collision-risk vessels from a microscopic perspective while providing insights into maritime traffic surveillance from a macro perspective.

Map Construction and Positioning Method for LiDAR SLAM-Based Navigation of an Agricultural Field Inspection Robot

In agricultural field inspection robots, constructing accurate environmental maps and achieving precise localization are essential for effective Light Detection And Ranging (LiDAR) Simultaneous Localization And Mapping (SLAM) navigation. However, navigating in occluded environments, such as mapping distortion and substantial cumulative errors, presents challenges. Although current filter-based algorithms and graph optimization-based algorithms are exceptionally outstanding, they exhibit a high degree of complexity. This paper aims to investigate precise mapping and localization methods for robots, facilitating accurate LiDAR SLAM navigation in agricultural environments characterized by occlusions. Initially, a LiDAR SLAM point cloud mapping scheme is proposed based on the LiDAR Odometry And Mapping (LOAM) framework, tailored to the operational requirements of the robot. Then, the GNU Image Manipulation Program (GIMP) is employed for map optimization. This approach simplifies the map optimization process for autonomous navigation systems and aids in converting the Costmap. Finally, the Adaptive Monte Carlo Localization (AMCL) method is implemented for the robot’s positioning, using sensor data from the robot. Experimental results highlight that during outdoor navigation tests, when the robot operates at a speed of 1.6 m/s, the average error between the mapped values and actual measurements is 0.205 m. The results demonstrate that our method effectively prevents navigation mapping distortion and facilitates reliable robot positioning in experimental settings.

Design and Implementation of a Shipborne Echo Sounder Simulator Based on a Seabed Echo Scattering and Noise Model

The Manila Amendment 2010 to the STCW International Convention has made clear requirements for seafarers to use the navigation simulation system for training. A shipborne echo sounder is an important navigation aid equipment necessary for a ship’s bridge. Proper use of this equipment can effectively prevent ship grounding accidents. Given the lack of research on simulating different seabed substrate echoes within echo sounder simulations, this paper proposes an algorithm for generating echoes and clutter from various seabed substrates, based on the Jackson model and noise model. Using the seabed echo generation algorithm, the bathymetric data and seabed echo under the influence of ship rolling are generated, the seabed echo simulation of the sounder under the influence of four different grazing angles and six different substrates is realized. Clutter images, including random noise, bubble interference, co-frequency interference, and fish school interference, are also simulated. A typical ship echo sounder simulator is designed and developed. The echo sounder simulator developed in this paper has high realism in seabed echoes and clutter simulation, complete functions, and friendly human–computer interaction. The system has been used by college students and crews, with satisfactory results, which can effectively meet the needs of actual training of seafarers.

A spatial data model of blind outdoor navigation for path optimization

Current navigational aids for blind people do not provide spatial information that meets the requirements of blind and visually impaired people (BVIP) for travel, and traditional map-based navigation services cannot be used directly for navigation. The purpose of this paper is to establish a spatial data model that aligns with their outdoor travel requirements to assist them in accessing spatial information. In alignment with the analysis of spatial information requirements for blind people during outdoor travel, the proposed data model divides the outdoor space into the path layer, the functional layer, the obstacle layer, and the transport and weather layer. Areas such as schools and sports fields, which fulfill certain requirements for them, are categorized as functional features. Essential public transportation stations for outdoor travel are included in transport station features, while obstacles that pose threats to their safety constitute obstacle features. Various features in space are spatially connected through different paths. The proposed semantic information properties enhance the information content representation of the features. The geometry of the features and the topological relationships between them are recorded and used for path planning and navigation in combination with the path layer. Finally, the eastern campus of Jiangxi University of Science and Technology served as an experimental area for the development of a prototype system based on the data model, and a case analysis was provided.

Influence of Runway Capacity and Air Traffic Capacity on the Growth of Aviation Business. Evidence From Wilson Airport, Kenya

The study focused on the effects of runway capacity and air traffic control on the growth of aviation businesses. The guiding objectives of this study were: to determine the effect of runway capacity on the aviation business growth in Kenya and to evaluate the effect of air traffic control capacity on aviation business growth in Kenya. The study was guided by resource-based theory. The study employed an explanatory research design. The study targeted 117 respondents comprising 92 operational managers at Wilson Airport, 25 air traffic controls, and Kenya Airport Authority employees based at Wilson Airport. A Census survey was used in this study to collect information from all participants in the population. The study collected primary data using questionnaires. In testing for reliability, Cronbach’s alpha coefficient was applied. Statistical Package for the Social Sciences (SPSS) version was used for data analysis. The study findings revealed that runway capacity positively and significantly affects aviation business growth. Air traffic control capacity has a positive and significant effect on aviation business growth). It can be concluded that runway capacity at Wilson Airport is insufficient. Night-hour flying can enhance runway capacity, and by large, aviation growth as AOC holders can fly more due to increased operating hours. The aerodrome owner and operator should ensure that it boosts the existing runway capacity either by optimizing the operations or expanding to cater to business growth. KAA and KCAA, the regulators, should consider boosting the runway capacity through increasing navigation aids to enable the introduction of night flying. The study recommends that future researcher’s study on the influence of public, and private partnerships to increase the ground movement capacity on aviation growth can also be conducted

Shock Me The Way: Directional Electrotactile Feedback under the Smartwatch as a Navigation Aid for Cyclists

Cycling navigation is a complex and stressful task as the cyclist needs to focus simultaneously on the navigation, the road, and other road users. We propose directional electrotactile feedback at the wrist to reduce the auditory and visual load during navigation-aided cycling. We designed a custom electrotactile grid with 9 electrodes that is clipped under a smartwatch. In a preliminary study we identified suitable calibration settings and gained first insights about a suitable electrode layout. In a subsequent laboratory study we showed that a direction can be encoded with a mean error of 19.28\,° (σ = 42.77°) by combining 2 adjacent electrodes. Additionally, by interpolating with 3 electrodes a direction can be conveyed with a similar mean error of 22.54° (σ = 43.57°). We evaluated our concept of directional electrotactile feedback for cyclists in an outdoor study, in which 98.8% of all junctions were taken correctly by eight study participants. Only one participant deviated substantially from the optimal path, but was successfully navigated back to the original route by our system.

Development and Application of an Advanced Automatic Identification System (AIS)-Based Ship Trajectory Extraction Framework for Maritime Traffic Analysis

This study addresses the challenges of maritime traffic management in the western waters of Taiwan, a region characterized by substantial commercial shipping activity and ongoing environmental development. Using 2023 Automatic Identification System (AIS) data, this study develops a robust feature extraction framework involving data cleaning, anomaly trajectory point detection, trajectory compression, and advanced processing techniques. Dynamic Time Warping (DTW) and the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) algorithms are applied to cluster the trajectory data, revealing 16 distinct maritime traffic patterns, key navigation routes, and intersections. The findings provide fresh perspectives on analyzing maritime traffic, identifying high-risk areas, and informing safety and spatial planning. In practical applications, the results help navigators optimize route planning, improve resource allocation for maritime authorities, and inform the development of infrastructure and navigational aids. Furthermore, these outcomes are essential for detecting abnormal ship behavior, and they highlight the potential of route extraction in maritime surveillance.

Exploring the Use of Landmarks to Aid Pedestrian Wayfinding

When wayfinding with mobile maps, the acquisition of spatial knowledge can be limited by relying on automated route instructions and the small map on the screen. Repeating a route without support from navigation aids may be challenging as the user has been focused on their mobile phone and not the surroundings. According to theories of spatial knowledge acquisition, landmarks are environmental elements important in the development of such knowledge. This study examines how different navigation aids impact spatial knowledge, with a particular focus on landmarks. Participants navigated a route using one of three aids: a booklet of sequential landmarks, a booklet of Google Maps screenshots, or a paper map. The landmarks were selected based on their conspicuity and strategic placement along the route. Thirty participants completed tasks assessing their spatial knowledge of the route and surrounding area after walking it. This study, divided into three phases, compared the effectiveness of each navigation aid, highlighting the effectiveness of landmarks in wayfinding. Results indicate that landmarks significantly enhance wayfinding, especially for pedestrians navigating short, pre-set routes without a map. This suggests that incorporating landmarks into mobile maps could improve on-screen spatial information.

An Experimental Study of Odometer as a Navigation aid for Land Vehicle Application

Strap-down inertial navigation system (SINS) shall provide position, velocity, and orientation information with reference to a pre-defined reference frame. The SINS shall have excellent accuracy over a short duration and is highly self-contained. However, the errors in navigation solutions build up exponentially with time and make the system output very unstable. In order to mitigate these errors, there is a need for a damping mechanism through external aiding sensors. In this article, one such approach is proposed to improve navigation accuracy for land vehicles in the GNSS (Global Navigation Satellite Systems) denied environment. The design and implementation of an odometer are carried out with the use of inductive proximity sensors and a mounting assembly to attach the odometer to one of the non-steering wheels of a vehicle. The odometer gives the pulse-high and pulse-low output with reference to the rotation of the wheel to which it is attached. Vehicle ground velocity is derived through sensed output pulses processed through quadrature decoder circuitry. Odometer measurements along with non-holonomic constraints (NHC) are used for minimizing velocity and position errors in SINS using an extended Kalman Filter (EKF) technique. Field trials are carried out to validate the proposed scheme of hybrid navigation with odometer design and experimental results are presented with a positioning accuracy of 0.05 % of distance travelled (DT).

Towards neuroadaptive navigation assistance to reduce spatial de-skilling

Maps have been invaluable navigation aids for millennia and thus have been critical for human survival. The increasing popularity of and high dependence on digital, location-aware assistive navigation technology, however, has been shown to divert our attention from the environment and to negatively influence innate spatial abilities. To mitigate this, neuroadaptive mobile geographic information displays (namGIDs) are proposed that respond in real-time to navigators’ cognitive task demands and wayfinder’s situated visuo-spatial attention needs. In doing so, namGIDs may not only help navigators maintain navigation efficiency but more importantly, also continuously scaffold spatial learning. To do this, the proposed navigation assistance must strike the appropriate balance between welcomed mobility efficiency gains while limiting human spatial deskilling. Leveraging neuroadaptive cartography, we can ensure to remain effective navigators, empowered to explore the world with confidence.

Pit builders are assisted by walls to find suitable sites for pit construction but are slowed down by obstacles and their initial distance from the destination

Abstract Habitat selection plays a critical role in the survival and reproduction of animals, with implications for all important behaviours. Animals are often limited in their familiarity with their habitat and rely on their senses and the habitat structure to detect suitable sites to settle in. We focus here on a trap‐building predator, the wormlion, which constructs pitfall traps in loose soil, and examine how the distance from suitable microhabitats and the presence of obstacles affect its habitat selection. We conducted four experiments. Experiment 1 assessed the impact of distance on the probability of wormlions reaching a suitable microhabitat. Experiment 2 examined the interaction between distance and obstacles. Experiment 3 investigated the influence of walls on the probability of reaching destinations. Experiment 4 evaluated walls as either leading paths or barriers. Our results showed that increasing distance from the destination negatively affected the probability of wormlions reaching it, with larger individuals more likely to cover greater distances. Obstacles interacted with distance, generally decreasing movement when present. Walls positively influenced orientation, aiding wormlions in reaching suitable sites, either by following the wall or locating the destination along the wall. The function of walls varied, sometimes facilitating movement and sometimes decreasing it, depending on their orientation and context. These findings suggest that walls may serve as navigational aids for wormlions in urban environments, assisting them in locating suitable microhabitats. This has implications for understanding habitat selection in urban ecosystems. Future research should explore the long‐term effects of walls on wormlion survival and habitat quality in more natural settings.

Evaluation of DME network capability using combination of rule-based model and gradient boosting regression

The future development of aeronautical navigation foresees an infrastructure rationalization of radionavigation aids with the aim of maintaining only the Minimum Operational Network, which brings benefits in terms of operational cost savings, promotes sustainability and optimal use of the radio spectrum. To ensure that the necessary navigation performance is preserved, the Distance Measuring Equipment (DME) plays a significant role, as DME/DME navigation is a short-term contingency solution when Global Navigation Satellite System is unavailable. Therefore, new DME ground stations are put into operation even though other navigation aids are being decommissioned at the same time. This paper addresses a question of possible DME network rationalization by developing a software model using a combination of a rule-based model, approximating of airborne DME interrogators interacting with DME ground transponders, with the implementation of the Gradient Boosting Regression to predict load of DME ground stations. The model is validated by comparing the results with the real load data obtained from an Air Navigation Service Provider. Several test cases are performed to evaluate the capability of the European DME network, simulating a reduction in the number of en-route DME stations and increases in air traffic using clustering methods. The results show that the ground station load limit was rarely reached, demonstrating the robustness and the potential for rationalization of the DME infrastructure.

Ship Detection in Synthetic Aperture Radar Images under Complex Geographical Environments, Based on Deep Learning and Morphological Networks.

Synthetic Aperture Radar (SAR) ship detection is applicable to various scenarios, such as maritime monitoring and navigational aids. However, the detection process is often prone to errors due to interferences from complex environmental factors like speckle noise, coastlines, and islands, which may result in false positives or missed detections. This article introduces a ship detection method for SAR images, which employs deep learning and morphological networks. Initially, adaptive preprocessing is carried out by a morphological network to enhance the edge features of ships and suppress background noise, thereby increasing detection accuracy. Subsequently, a coordinate channel attention module is integrated into the feature extraction network to improve the spatial awareness of the network toward ships, thus reducing the incidence of missed detections. Finally, a four-layer bidirectional feature pyramid network is designed, incorporating large-scale feature maps to capture detailed characteristics of ships, to enhance the detection capabilities of the network in complex geographic environments. Experiments were conducted using the publicly available SAR Ship Detection Dataset (SSDD) and High-Resolution SAR Image Dataset (HRSID). Compared with the baseline model YOLOX, the proposed method increased the recall by 3.11% and 0.22% for the SSDD and HRSID, respectively. Additionally, the mean Average Precision (mAP) improved by 0.7% and 0.36%, reaching 98.47% and 91.71% on these datasets. These results demonstrate the outstanding detection performance of our method.

Landmark-based guidance and cognitive saliency: Age-related benefits in spatial performance

Older adults have difficulties using a map, and the use of GPS systems seems beneficial to help them find their way in cities. The question arises however as to what extent the introduction of landmarks can be even more beneficial. While the visual saliency of landmarks has been well studied, the cognitive saliency of landmarks has received little attention. Our objective in this study was to determine if guiding young and older pedestrians with visually and cognitively salient landmarks inserted in a map or a GPS-like system improved spatial performances. Thirty-four young and 32 older adults navigated a virtual environment using a joystick. They were guided with a map or with GPS-like instructions, including either only visually or both visually and cognitively salient landmarks. After each itinerary, participants completed four tasks: landmark recognition and sequencing, direction recognition and sequencing. The results showed that the integration of visually and cognitively salient landmarks in a map or in GPS-like instructions improved the construction of landmark and route knowledge in both young and older participants. Results also suggested that age-related deficits in spatial memory could be reduced by using GPS-like instructions or by introducing cognitively salient landmarks, in a map or in a GPS-like system. This research opens several perspectives for research as well for the design of human-centred navigation aids.