Search results

X-ray pulsar navigation (XPNAV) is an autonomous celestial navigation technology for deep space missions. The error in the pulse time of arrival used in pulsar navigation is large for various practical reasons and thus greatly reduces the navigation accuracy of spacecraft near the Earth and in deep space. This paper aims to propose a novel method based on ranging information that improves the performance of XPNAV.

This method replaces one pulsar observation with a satellite observation. The ranging information is the difference between the absolute distance of the satellite relative to the spacecraft and the estimated distance of the satellite relative to the spacecraft. The proposed method improves the accuracy of XPNAV by combining the ranging information with the observation data of two pulsars.

The simulation results show that the proposed method greatly improves the XPNAV accuracy by 70% compared with the conventional navigation method that combines the observations of three pulsars. This research also shows that a larger angle between the orbital plane of the satellite and that of the spacecraft provides higher navigation accuracy. In addition, a greater orbital altitude difference implies higher navigation accuracy. The position error and ranging error of the satellite have approximately linear relationships with the navigation accuracy.

The novelty of this study is that the satellite ranging information is integrated into the pulsar navigation by using mathematical geometry.

Because the voice-to-technology (V2T) encounter remains under-theorised, the purpose of this paper is to overcome this gap by investigating customers use of the interactive voice response (IVR) system and “the customer journey” through the call centre service system.

From an interpretive study of a UK call centre, the metaphorical aspects of language used to represent the service process are analysed, accompanied by an examination of how the servicescape dimensions of spatial layout and signs are constituted in the call centre service process, and the resulting implications for virtual-aural navigation.

Despite no physical movement, customers represent their experience of navigating “through” the service process in spatial terms. Therefore, understanding precisely how servicescape dimensions are reconfigured within the virtual-aural setting of the call centre is necessary to appreciate customer experience of V2T but also voice-to-voice (V2V) encounters. The call centre servicescape lacks a spatial representation of layout and signs that would conventionally support navigation and purposeful movement.

Despite observing live calls, direct interaction with customers was not possible. The paper was based upon a single case study, and the hermeneutic focus on understanding and meaning meant that the study did not emphasise the quantification of phenomenon. Therefore, further research on virtual navigation is required.

Problematic V2T encounters compromise the quality and efficiency of service provision. A visual representation of the IVR system may possibly support V2T encounters, while encouraging customer service advisors to act as “guides” during V2V encounters may reduce problems emerging from V2T encounters.

First, an original theorisation of the customer experience of the V2T encounter is provided through the theoretical notion of spatialisation metaphors. Second, a preliminary conceptualisation of the call centre servicescape is developed, which shows how spatial layout and signs are reconfigured and represented in this virtual-aural setting.

The paper aims to investigate how a tablet's design features, namely, its navigation design and visual appearance, influence users' enjoyment, concentration and control, when using tablets for problem-solving, and thereafter how their core flow experiences impact their perceived performance and efficiency with problem-solving.

This study uses a field survey approach to engage 87 participants in a decision sciences class to use eTextbooks and a few other associated educational apps including CourseSmart app for e-notes and highlighting, sketchbook app and a calculator app in tablets to resolve class problems at a large US university.

This study finds that the tablet's interface design features (navigation and visual appearance) make users engrossed in their problem-solving processes with perceived enjoyment, concentration and control. This, in turn, impacts their perceived performance and efficiency. Moreover, visual appearance plays the most significant role in arousing users' affective emotions (i.e. enjoyment), while interface navigation is crucial to engage users' deep concentration (i.e. cognition) and control for problem-solving.

Modern tablets are being used widely in various sectors. More in-depth user flow experience design associated with tablet use for problem-solving contexts should be further advocated in order to provide more engaging and meaningful flow experiences to users.

This study shows that the design of the tablet interface can engage users in problem-solving processes in both affective and cognitive ways. It provides valuable insights on tablet interface design for problem-solving.

As health care delivery becomes increasingly focused on patient-centered models, interventions such as patient navigation that have the potential to improve care coordination garner interest from health care managers and clinicians. The ability to understand how and to what extent patient navigation is successful in addressing coordination issues, however, is hampered by multiple definitions, vague boundaries, and different contextual implementations of patient navigation. Using a systematic review strategy and classification method, we review both the conceptual and empirical literature regarding navigation in multiple clinical contexts. We then describe and conceptualize variation in how patient navigation has been defined, implemented, and theorized to affect outcomes. This review suggests that patient navigation varies along multiple dimensions and that the variation is related to differing resources, constraints, and goals. We propose a conceptual model to frame further research and suggest that research in this area must carefully account for this variation in order to accurately assess the benefits of patient navigation and provide actionable knowledge for managers.

Indoor localization is a key tool for robot navigation in indoor environments. Traditionally, robot navigation depends on one sensor to perform autonomous localization. This paper aims to enhance the navigation performance of mobile robots, a multiple data fusion (MDF) method is proposed for indoor environments.

Here, multiple sensor data i.e. collected information of inertial measurement unit, odometer and laser radar, are used. Then, an extended Kalman filter (EKF) is used to incorporate these multiple data and the mobile robot can perform autonomous localization according to the proposed EKF-based MDF method in complex indoor environments.

The proposed method has experimentally been verified in the different indoor environments, i.e. office, passageway and exhibition hall. Experimental results show that the EKF-based MDF method can achieve the best localization performance and robustness in the process of navigation.

Indoor localization precision is mostly related to the collected data from multiple sensors. The proposed method can incorporate these collected data reasonably and can guide the mobile robot to perform autonomous navigation (AN) in indoor environments. Therefore, the output of this paper would be used for AN in complex and unknown indoor environments.

This paper aims to present a hybrid control approach that combines learning-based reactive control and affordance-based deliberate control for autonomous mobile robot navigation. Unlike many current navigation approaches which only use learning-based paradigms, the authors focus on how to utilize the machine learning methods for reactive control together with the affordance knowledge that is simultaneously inherent in natural environments to gain advantages from both local and global optimization.

The idea is to decompose the complex and large-scale robot navigation task into multiple sub-tasks and use the hierarchical reinforcement learning (HRL) algorithm, which is well-studied in the learning and control algorithm domains, to decompose the overall task into sub-tasks and learn a grid-topological map of the environment. An affordance-based deliberate controller is used to inspect the affordance knowledge of the obstacles in the environment. The hybrid control architecture is then designed to integrate the learning-based reactive control and affordance-based deliberate control based on the grid-topological and affordance knowledge.

Experiments with computer simulation and an actual humanoid NAO robot have demonstrated the effectiveness of the proposed hybrid approach for mobile robot navigation.

The main contributions of this paper are a new robot navigation framework that decomposes a complex navigation task into multiple sub-tasks using the HRL approach, and hybrid control architecture development that integrates learning-based and affordance-based paradigms for autonomous mobile robot navigation.

This article proposes the concept of web clientserver event together with its associated taxonomy which yields a formal specification for such an event. The concept, in conjunction with the concept of atomic use case (reviewed in the article), is then used as a key element for a model‐driven approach to web information system development. The outcome is a new method for web information systems development that reduces the complex web‐based hypermedia navigation behaviour to a much simpler event‐driven behaviour. On the strength of that realized simplicity, the method provides (i) a set of platform‐independent models that completely characterizes the application, and (ii) a well‐defined process to map the combined model to any chosen platform‐dependent implementation.

To create a benchmark for design evaluation of commercial web sites, to model customers' site navigation behavior, and to develop and implement algorithms for link‐structure personalization.

The principal methodology used for design benchmarking is a survey of corporate web sites of some US Fortune 500 companies and top Indian companies and statistical analysis of the data so collected. The principal methodological approach for modeling user behavior, user's interest and algorithms for link‐structure personalization, is the development of a Markov decision process (MDP) in the overall framework of a semi‐Markov model and implementing the same in a link‐structure personalization system.

It is observed that the functional web site features significantly differ for the sites dealing with various product categories whereas the non‐functional features do not. The over‐stressed or under‐stressed features in the Indian web sites are found. The statistics generated from the user behavior model are validated against the real life user behavior and found satisfactory. The appropriateness of the link‐structure personalization algorithms is established by comparing the set of links generated by the algorithm with the links generated by the optimal policy of the underlying MDP.

The corporate that have been considered are conglomerates offering a number of products and services. But we categorize these sites based on their major product offering. Our approach of modeling the user behavior as a semi‐Markov process is possible because of our advanced implementation infrastructure. Undesirable network effects like delays, bandwidth, etc. may not make such a model that attractive in a very traditional type of environment. But the data collected in such environment can still be mined after adequate pre‐processing and appropriate normalization

Using the benchmark proposed in this model a webmaster can evaluate his web site. The sites with low site evaluation index can be improved by adding features with high weight depending on the product offering of the company. Webmaster can design the three level information architecture described in the paper and subsequently implement link‐structure personalization algorithm to improve site navigability. Besides improving site navigability the user behavior data collected thereon can be mined to generate other valuable information.

To assess and enhance the usability of an ecommerce site our work proposes: a benchmark to evaluate commercial web site design; a stochastic model to study and understand user behavior; an algorithm to personalize link‐structure of a commercial web site, and a general framework to implement a link‐structure personalization system.

This paper aims to present a system that is fully capable of addressing the issue of detection, tracking and following pedestrians, which is a very challenging task, especially when it is considered for using in large outdoors infrastructures. Three modules, detection, tracking and following, are integrated and tested over long distances in semi-structured scenarios, where static or dynamic obstacles, including other pedestrians, can be found.

The detection is based on the probabilistic fusion of a laser scanner and a camera. The tracking module pairs observations with previously detected targets by using Kalman Filters and a Mahalanobis-distance. The following module allows to safely pursue the target by using a well-defined navigation scheme.

The system can track pedestrians from static position to 3.46 m/s (running). It handles occlusions, crossings or miss-detections, keeping track of the position even if the pedestrian is only detected in 55/per cent of the observations. Moreover, it autonomously selects and follows a target at a maximum speed of 1.46 m/s.

The main novelty of this study is the integration of the three algorithms in a fully operational system, tested in real outdoor scenarios. Furthermore, the addition of labelling to the detection algorithm allows using the full range of a single sensor while preserving the high performance of a combined detection. False-positives’ rate is reduced by handling the uncertainty level when pairing observations. The inclusion of pedestrian speed in the model speeds up and simplifies tracking process. Finally, the most suitable target is automatically selected by a scoring system.

The purpose of this paper is to present the development of hardware‐in‐the‐loop simulation (HILS) for visual target tracking of an octorotor unmanned aerial vehicle (UAV) with onboard computer vision.

HILS for visual target tracking of an octorotor UAV is developed by integrating real embedded computer vision hardware and camera to software simulation of the UAV dynamics, flight control and navigation systems run on Simulink. Visualization of the visual target tracking is developed using FlightGear. The computer vision system is used to recognize and track a moving target using feature correlation between captured scene images and object images stored in the database. Features of the captured images are extracted using speed‐up robust feature (SURF) algorithm, and subsequently matched with features extracted from object image using fast library for approximate nearest neighbor (FLANN) algorithm. Kalman filter is applied to predict the position of the moving target on image plane. The integrated HILS environment is developed to allow real‐time testing and evaluation of onboard embedded computer vision for UAV's visual target tracking.

Utilization of HILS is found to be useful in evaluating functionality and performance of the real machine vision software and hardware prior to its operation in a flight test. Integrating computer vision with UAV enables the construction of an unmanned system with the capability of tracking a moving object.

HILS for visual target tracking of UAV described in this paper could be applied in practice to minimize trial and error in various parameters tuning of the machine vision algorithm as well as of the autopilot and navigation system. It also could reduce development costs, in addition to reducing the risk of crashing the UAV in a flight test.

A HILS integrated environment for octorotor UAV's visual target tracking for real‐time testing and evaluation of onboard computer vision is proposed. Another contribution involves implementation of SURF, FLANN, and Kalman filter algorithms on an onboard embedded PC and its integration with navigation and flight control systems which enables the UAV to track a moving object.