Advanced Navigation Research Articles

The impact of design on improved learning in virtual worlds: an experimental study.

Virtual worlds are the most advanced form of virtual environments, which offer one of the best platforms for serving various domains. They are, especially, well suited for education, to cope with the physical restrictions imposed due to COVID-19 outbreak, as they offer classroom experience to their users through immersion. They are online interactive spaces which are collaborative, persistent, coherent, and social in nature. Users immersed in these spaces are represented in the form of digital characters called, avatars. Virtual worlds offer advanced navigation methods such as flying and teleporting to facilitate quick learning. This paper analyses the use of a partial but carefully reconstructed cultural heritage site, developed in OpenSimulator framework, for learning both in terms of discourse and quantitative analysis. Discourse analysis compares the developed virtual world presence with traditional content provisioning methods in terms of a large set of well-known characteristics. Quantitative analysis, on the other hand, is based on data collected from users after conducting simple learning experiments. It revealed that the properties such as realism, friendliness, advanced navigation, and being detailed and social in nature greatly attracted user attention in learning. The learning was fast compared with traditional methods, however, it was a little hard for naive users to start exploring the content. Pre and post learning responses of users revealed that their knowledge level was significantly increased. Based on valuable suggestions, it is planned in future, to add intelligence to traditional agents, so they may help in an increased learning experience of users, based on the knowledge gained in earlier sessions.

P56 Early Health Technology Assessment to Guide Introduction of Novel Technology into the Market: The Vostars System Case Study

The aim of the study is to show potential approaches and usefulness of early Health Technology Assessment exemplifying the case study of the Video and Optical See-Through Augmented Reality Surgical System (VOSTARS), an advanced navigation tool for non-endoscopic surgeries, recently developed, also thanks to funding from H2020 programme.

Aided Diver Navigation Using Autonomous Vehicles in Simulated Underwater Environment*

Man's admiration of the underwater world has been recorded ever since ancient times and to this day, it does not cease to amaze large sections of modern society. Whether for recreational or sport purposes, commercial activities or strategic military operations, the underwater environment plays an amusing yet inhospitable host to its many explorers. Knowledge and respect for our oceans are keys for a sustainable and safe relationship between humans and the underwater. People have often used their ingenuity for adaptation to various environments and the technology for allowing divers to reach extreme places in a safe manner is developing rapidly. This paper will investigate benefits of using robots as diving buddies for aiding underwater navigation. In a typical dive mission scenario, a diver is given relative distance and bearings to an underwater target as he tries to overcome environmental influences to navigate to that target using customary diving equipment; a compass and diving computer/watch. Diving robots can introduce sensors capable of achieving advanced navigation and guiding divers even in low visibility conditions. The experiment in this paper compares these two approaches and validates the results in a simulation environment on 26 participants. The success rate in finding and reaching the targets are compared in terms of time and distance travelled. Finally, the simulation tools are evaluated by participants as well as its potential in developing algorithms and user training using a NASA-TLX workload estimation scale.

Performance Analyses of a RAIM Algorithm for Kalman Filter with GPS and NavIC Constellations.

This paper evaluates the performance of an integrity monitoring algorithm of global navigation satellite systems (GNSS) for the Kalman filter (KF), termed KF receiver autonomous integrity monitoring (RAIM). The algorithm checks measurement inconsistencies in the range domain and requires Schmidt KF (SKF) as the navigation processor. First, realistic carrier-smoothed pseudorange measurement error models of GNSS are integrated into KF RAIM, overcoming an important limitation of prior work. More precisely, the error covariance matrix for fault detection is modified to capture the temporal variations of individual errors with different time constants. Uncertainties of the model parameters are also taken into account. Performance of the modified KF RAIM is then analyzed with the simulated signals of the global positioning system and navigation with Indian constellation for different phases of aircraft flight. Weighted least squares (WLS) RAIM used for comparison purposes is shown to have lower protection levels. This work, however, is important because KF-based integrity monitors are required to ensure the reliability of advanced navigation methods, such as multi-sensor integration and vector receivers. A key finding of the performance analyses is as follows. Innovation-based tests with an extended KF navigation processor confuse slow ramp faults with residual measurement errors that the filter estimates, leading to missed detection. RAIM with SKF, on the other hand, can successfully detect such faults. Thus, it offers a promising solution to developing KF integrity monitoring algorithms in the range domain. The modified KF RAIM completes processing in time on a low-end computer. Some salient features are also studied to gain insights into its working principles.

Vehicle Navigation System based on Pollution Metric Analysis with Q-Learning Algorithm

The navigation systems available in the present scenario takes into account the path distance for their estimations. In some advanced navigation systems, the road traffic analysis is also considered in the algorithm for their predictions. The proposed work estimates a navigation path with respect to the present pollution level on the roadways. The work suggests an alternate path to avoid additional vehicles to enter the same road which is already impacted by air pollution. A Q-learning (Quality learning) prediction algorithm is trained in the proposed work with a self-made dataset for the estimations. The experimental work presented in the paper explores the accuracy and computational speed of the developed algorithm in comparison to the traditional algorithms.

Performance of UAV-Based Digital Orthophoto Generation for Emergency Response Applications

Unmanned Aerial Vehicles (UAVs) have been used for accurate orthophoto generation based on advanced Global Navigation Satellite System (GNSS) techniques. In recent years, the UAV systems have become an effective tool for fast monitoring of damages caused by disasters such as the earthquake hazards. The conventional orthophoto generation based on ground control points takes too much time during emergency situations. In the study, different methodologies for the processing of the acquired GNSS Positioning data for direct georeferencing of UAVs were investigated in terms of various orbit products. Evaluating the fitness for emergency response applications, the ground control points (GCPs) also used for validation of the generated orthophoto without using GCPs and based on Precise Point Positioning (PPP) approach. In this study, Ultra-Rapid, Rapid and Final PPP methods based on GNSS observations were used for direct geo-referencing. Thirteen GCPs were located at the study area for the validation of the orthophoto accuracy generated by direct geo-referencing.

Augmented Reality and Intraoperative Navigation in Sinonasal Malignancies: A Preclinical Study.

ObjectiveTo report the first use of a novel projected augmented reality (AR) system in open sinonasal tumor resections in preclinical models and to compare the AR approach with an advanced intraoperative navigation (IN) system.MethodsFour tumor models were created. Five head and neck surgeons participated in the study performing virtual osteotomies. Unguided, AR, IN, and AR + IN simulations were performed. Statistical comparisons between approaches were obtained. Intratumoral cut rate was the main outcome. The groups were also compared in terms of percentage of intratumoral, close, adequate, and excessive distances from the tumor. Information on a wearable gaze tracker headset and NASA Task Load Index questionnaire results were analyzed as well.ResultsA total of 335 cuts were simulated. Intratumoral cuts were observed in 20.7%, 9.4%, 1.2,% and 0% of the unguided, AR, IN, and AR + IN simulations, respectively (p < 0.0001). The AR was superior than the unguided approach in univariate and multivariate models. The percentage of time looking at the screen during the procedures was 55.5% for the unguided approaches and 0%, 78.5%, and 61.8% in AR, IN, and AR + IN, respectively (p < 0.001). The combined approach significantly reduced the screen time compared with the IN procedure alone.ConclusionWe reported the use of a novel AR system for oncological resections in open sinonasal approaches, with improved margin delineation compared with unguided techniques. AR improved the gaze-toggling drawback of IN. Further refinements of the AR system are needed before translating our experience to clinical practice.

A new inertial navigation system for guiding implant placement. An in-vitro proof-of-concept study.

The aim of this study was to assess the potential use of a new advanced inertial navigation system for guiding dental implant placement and to compare this approach with standard stereolithographic template guiding. A movement processing unit with a 9-axis absolute orientation sensor was adapted to a surgical handpiece and wired to a computer navigation interface. Sixty implants were placed by 10 operators in 20 jaw models. The 30 implants of the test group were placed in 10 models guided by the new inertial navigation prototype. The 30 implants of the control group were placed in another 10 models using a CAD-CAM template. Both groups were subdivided into experienced and non-experienced operators. Pre- and postoperative computer tomography images were obtained and matched to compare the planned and final implant positions. Four deviation parameters (global, angular, depth, and lateral deviation) were defined and calculated. The primary outcome was the angular deviation between the standard stereolithographic approach and the new inertial navigation system. Results showed no significant differences between both groups, suggesting that surgical navigation based on inertial measurement units (IMUs) could potentially be useful for guiding dental implant placement. However, more studies are still needed to translate this new approach into clinical practice.

Advanced Navigation Control Systems

Compared to the other major modes of transportation aircraft is the fastest mode till now with few challenges. The major and important challenge is the safety of passengers. A small mistake regarding safety operations in aviation leads to demise of passengers and crew. In recent times and in history many flights had gone missing and highjacked. Even the information about some of the flights were unknown till now. We even had a history about the airlines that pay-off a huge indemnity for an air crash. Various navigation systems are present with the advanced navigation techniques from GPS to satellite navigation with many limitations. There are even many safety considerations and advanced techniques that are in effect for the safety of passengers but the plane crashes had not been nullified. There is a need to improve the safety procedures and navigation systems for the safety of flights. This paper presents the information about the safe navigation systems that enables the safe flight. These methods and techniques are suggested based on the research and analysis of various missing flights and flight crashes. Using these navigation systems, highjack, flight crashes, missing flights can be reduced to a great extent. By incorporating these methods and systems on board, flight will be safer.

Prevalence of spine surgery navigation techniques and availability in Africa: A cross-sectional study

BackgroundAfrica has a large burden of spine pathology but has limited and insufficient infrastructure to manage these spine disorders. Therefore, we conducted this e-survey to assess the prevalence and identify the determinants of the availability of spine surgery navigation techniques in Africa. Materials and methodsA two-part questionnaire was disseminated amongst African neurological and orthopedic surgery consultants and trainees from January 24 to February 23, 2021. The Chi-Square, Fisher Exact, and Kruskal-Wallis tests were used to evaluate bivariable relationships, and a p-value <0.05 was considered statistically significant. ResultsWe had 113 respondents from all regions of Africa. Most (86.7 %) participants who practiced or trained in public centers and centers had an annual median spine case surgery volume of 200 (IQR = 190) interventions. Fluoroscopy was the most prevalent spine surgery navigation technique (96.5 %), followed by freehand (55.8 %), stereotactic without intraoperative CT scan (31.9 %), robotic with intraoperative CT scan (29.2 %), stereotactic with intraoperative CT scan (8.8 %), and robotic without intraoperative CT scan (6.2 %). Cost of equipment (94.7 %), lack of trained staff to service (63.7 %), or run the equipment (60.2 %) were the most common barriers to the availability of spine instrumentation navigation. In addition, there were significant regional differences in access to trained staff to run and service the equipment (P = 0.001). ConclusionThere is a need to increase access to more advanced navigation techniques, and we identified the determinants of availability.

Image-Based Deep Reinforcement Meta-Learning for Autonomous Lunar Landing

Future exploration and human missions on large planetary bodies (e.g., moon, Mars) will require advanced guidance navigation and control algorithms for the powered descent phase, which must be capable of unprecedented levels of autonomy. The advent of machine learning, and specifically reinforcement learning, has enabled new possibilities for closed-loop autonomous guidance and navigation. In this paper, image-based reinforcement meta-learning is applied to solve the lunar pinpoint powered descent and landing task with uncertain dynamic parameters and actuator failure. The agent, a deep neural network, takes real-time images and ranging observations acquired during the descent and maps them directly to thrust command (i.e., sensor-to-action policy). Training and validation of the algorithm and Monte Carlo simulations shows that the resulting closed-loop guidance policy reaches errors in the order of meters in different scenarios, even when the environment is partially observed, and the state of the spacecraft is not fully known.

POWERED LANDING GUIDANCE ALGORITHMS USING REINFORCEMENT LEARNING METHODS FOR LUNAR LANDER CASE

Any future planetary landing missions, just as demonstrated by Perseverance in 2021 Mars landing missions require advanced guidance, navigation, and control algorithms for the powered landing phase of the spacecraft to touch down a designated target with pinpoint accuracy (circular error precision < 5 m radius). This requires a landing system capable to estimate the craft’s states and map them to certain thrust commands for each craft’s engine. Reinforcement learning theory is used as an approach to manage the mapping guidance algorithm and translate it to engine thrust control commands. This work compares several reinforcement-learning-based approaches for a powered landing problem of a spacecraft in a two-dimensional (2-D) environment and identifies their advantages or disadvantages. Three methods in reinforcement learning, namely Q-Learning, and its extensions such as DQN and DDQN. They are benchmarked in terms of rewards and training time needed to land the Lunar Lander. It is found that the Q-Learning method also called Heuristic produced the highest efficiency. Another contribution of this paper is to show the combination usage of online weights � between the action selection process and action evaluation process, yields a higher reward, instead of separating them, which significantly enhances their optimization performance. The simulations of the powered guidance performance in a 2-D simulation environment highlight the effectiveness of DQN to handle multiple neural networks better than DDQN.

Real-time spatiotemporal prediction and imputation of traffic status based on LSTM and Graph Laplacian regularized matrix factorization

Accurate prediction of traffic status in real time is critical for advanced traffic management and travel navigation guidance. There are many attempts to predict short-term traffic flows using various deep learning algorithms. Most existing prediction models are only tested on spatiotemporal data assuming no missing data entries. However, this ideal situation rarely exists in real world due to sensor or network transmission failure. Missing data is a nonnegligible problem. Previous studies either remove time series with missing entries or impute missing data before building prediction models. The former may cause insufficient data for model training, while the latter adds extra computational burden and the imputation accuracy has direct impacts on the prediction performance. In this study, we propose an online framework that can make spatiotemporal predictions based on raw incomplete data and impute possible missing values at the same time. We design a novel spatial and temporal regularized matrix factorization model, namely LSTM-GL-ReMF, as the key component of the framework. The Long Short-term Memory (LSTM) model is chosen as the temporal regularizer to capture temporal dependency in time series data and the Graph Laplacian (GL) serves as the spatial regularizer to utilize spatial correlations among network sensors to enhance prediction and imputation performance. The proposed framework integrating with the LSTM-GL-ReMF model are tested and compared with other state-of-the-art matrix factorization models and deep learning models on three uni-variate and multi-variate spatiotemporal traffic datasets. The experimental results show our approach has a robust and accurate performance in terms of prediction and imputation accuracy under various data missing scenarios.

Present and Future Spinal Robotic and Enabling Technologies.

Enabling technologies include surgical planning software, computer-assisted navigation, intraoperative three-dimensional (3D) imaging, and robotic systems. Presently, these technologies are in various stages of refinement. Spinal robots in particular are currently limited to the positioning of an alignment guide for pedicle screw placement. Current generation spinal robots, therefore, play a more limited role in spinal surgery. In contrast to spinal robots, intraoperative imaging technology has been developed further, to a stage that allows accurate 3D spinal image acquisition that can be readily utilized for spinal navigation. The integration of these various technologies has the potential to maximize the safety, consistency, reliability, and efficacy of surgical procedures. To that end, the trend for manufacturers is to incorporate various enabling technologies into the spinal robotic systems. In the near-term, it is expected that integration of more advanced planning software and navigation will result in wider applicability and value. In the long-term, there are a variety of enabling technologies such as augmented reality that may be a component of spinal robots. This article reviews the features of currently available spinal robots and discusses the likely future advancements of robotic platforms in the near- and long-term.

Application of Beidou Satellite Navigation System in Finding Separated Children

The Beidou satellite navigation system is currently one of the most advanced navigation systems on an international scale. The purpose of this work is to design a system framework based on the Beidou navigation system for the positioning and tracking of children. The novel system designed in this work includes a Beidou satellite system, a tracker assembly mounted on the sole of a child’s shoe, a guardian’s cell phone terminal and a monitoring computer terminal. In particular, the present work creates a new tracker assembly that is communicatively connected to the guardian’s mobile phone terminal and the monitoring computer terminal through the Beidou satellite system, respectively. This paper designs and implements an effective monitoring and tracking of children’s location based on Beidou navigation, which is worth promoting and applying

Autonomous Flight Trajectory Control System for Drones in Smart City Traffic Management

With the exponential growth of numerous drone operations ranging from infrastructure monitoring to even package delivery services, the integration of UAS in the smart city transportation systems is an actual task that requires radically new, sustainable (safe, secure, with minimum environmental impact and life cycle cost) solutions. The primary objective of this proposed option is the definition of routes as desired and commanded trajectories and their autonomous execution. The airspace structure and fixed routes are given in the global GPS reference system with supporting GIS mapping. The concept application requires a series of further studies and solutions as drone trajectory (or corridor) following by an autonomous trajectory tracking control system, coupled with autonomous conflict detection, resolution, safe drone following, and formation flight options. The second part of the paper introduces such possible models and shows some results of their verification tests. Drones will be connected with the agency, designed trajectories to support them with factual information on trajectories and corridors. While the agency will use trajectory elements to design fixed or desired trajectories, drones may use the conventional GPS, infrared, acoustic, and visual sensors for positioning and advanced navigation. The accuracy can be improved by unique markers integrated into the infrastructure.

High-Accuracy Optical Frequency Atomic Clock

Frequencies have been the most accurately measured physical quantity since the second was defined in 1967 based on the microwave atomic transition of a Cs atom. Recently, atomic clocks using optical frequency transitions have shown an order of magnitude better accuracy than microwave clocks. Thanks to their high accuracy and resolution, atomic clocks have become a new tool for investigations involving fundamental science and technology, such as the search for dark matter, gravitational wave detection, the temporal variation of fundamental constants, relativistic geodesy, quantum metrology, and the advanced Global Navigation Satellite System (GNSS). In addition, a redefinition of the second based on the optical frequency is expected. In this paper, we review the principles and applications of optical clocks.

Autonomous Underwater Vehicles and Field of View in Underwater Operations

Submarine inspections and surveys require underwater vehicles to operate in deep waters efficiently, safely and reliably. Autonomous Underwater Vehicles employing advanced navigation and control systems present several advantages. Robust control algorithms and novel improvements in positioning and navigation are needed to optimize underwater operations. This paper proposes a new general formulation of this problem together with a basic approach for the management of deep underwater operations. This approach considers the field of view and the operational requirements as a fundamental input in the development of the trajectory in the autonomous guidance system. The constraints and involved variables are also defined, providing more accurate modelling compared with traditional formulations of the positioning system. Different case studies are presented based on commercial underwater cameras/sonars, analysing the influence of the main variables in the measurement process to obtain optimal resolution results. The application of this approach in autonomous underwater operations ensures suitable data acquisition processes according to the payload installed onboard.

Peripherally Inserted Central Catheter (PICC) Insertion Success and Optimal Placement with New Technology: A Pre-Post Cohort Study

Highlights Abstract Background: Peripherally inserted central catheters (PICCs) are commonly placed with the assistance of fluoroscopy or medical imaging, ultrasound, electrocardiogram guidance, or all the above. Innovative ultrasound technologies continue to emerge; however, the impact upon clinical outcomes is not well understood. In this study, we aimed to compare outcomes of an existing ultrasound system with SHERLOCK 3CG™ Tip Confirmation (preintervention) to an updated SHERLOCK 3CG Diamond Tip Confirmation system, incorporating catheter-to-vein ratio measurement capabilities and an advanced magnetic-based tip navigation system (postintervention). Methods: In this prospective pre-post cohort study, we recruited adult patients requiring a new PICC. The study was conducted at a quaternary hospital in Queensland, Australia. Data were collected between May 2017 (4 months before equipment introduction) and January 2018 (4 months after equipment introduction), with a 1-month exclusion (education or learning) period in between. Patient, PICC, and device removal details were collected. The primary outcome was first-time insertion success, defined as successful PICC insertion after a single attempt (skin puncture), with the tip confirmed in an optimal location by the navigation system and a subsequent chest x-ray (as per hospital policy). Results: There were 503 participants with patient demographics and PICC characteristics balanced between the preintervention (n = 266) and postintervention (n = 237) groups. First-time insertion success was higher in the preintervention group (203/255, 80%) than the postintervention group (166/226, 73%), but this was not statistically significant (risk ratio = 0.92, 95% confidence interval = 0.83–1.02). Conclusions: There was no change in clinical outcomes with the use of next-generation ultrasound technology. These results justify future large studies and subsequent review into the efficacy of tip-confirmation systems and processes to maintain patient safety.

An integrated spatio-temporal analysis of emergency medical service response characteristics for stroke events across Alabama

IntroductionStroke treatment must be given within the first few hours of symptom onset, so rapid Emergency Medical Services (EMS) response is essential for positive patient outcomes. Examining EMS response characteristics across temporal and geographical perspectives is critical for improving Alabama's stroke death rate from its current 49th place in the U.S. MethodsWe examined EMS delay characteristics for patients with suspected strokes from 2018-2019 across Alabama, with particular attention paid to rural and urban differences. We used EMS call data from the Alabama Department of Public Health and defined possible stroke cases as calls where a stroke scale completed by EMS was positive or indeterminate. We coded the time between EMS dispatch and destination arrival as EMS delay. This study incorporates global and local spatio-temporal weighted ordered logistic regression models to evaluate significant non-stationary correlations of factors with EMS delay by accounting for unobserved heterogeneity. ResultsWe examined 17,088 possible stroke cases and found that 74% of these calls had total response times within 60 min. The longest EMS delay occurred in rural counties. EMS response characteristics, such as pre-arrival instructions and advanced vehicle navigation, were associated with shorter delays, while long travel distance and on-scene/transport times were associated with longer EMS delays. The impact of response characteristics on stroke-event-based EMS delay varied significantly across rural and urban counties and time (i.e., between 2018 and 2019). ConclusionThe revealed spatio-temporal correlations are useful for EMS personnel in applying effective localized rural and urban EMS response improvement strategies.