Fast Navigation Research Articles

Mathematics base for mobile robot navigation using mirror petri net Method

The movement of the robot will be even more challenging if on the mobile journey the robot gets a lot of obstacles, there are many choices to turn left or turn right and be able to go back to the place of origin, for that purpose precise and fast navigation is needed. This research offer new methods robot mobile navigation modeled using the mirror petri net method. This method is the development of the petri net method, which is a graphical and mathematical modeling method that is very suitable for modeling a contradictory movement system. The final result will be obtained a mathematical model with the same marking value, which is used as a mobile robot navigation. This same marking value will have a different meaning when departing and when return.

VR Locomotion in the New Era of Virtual Reality: An Empirical Comparison of Prevalent Techniques

The latest technical and interaction advancements within the virtual reality (VR) field have marked a new era, not only for VR, but also for VR locomotion. In this era, well-established, prevalent VR locomotion techniques are mostly used as points of comparison for benchmarking of new VR locomotion designs. At the same time, there is the need for more exploratory, comparative studies of contemporary VR locomotion techniques, so that their distinguished interaction aspects can be documented and guide the design process of new techniques. This article presents a comparative, empirical evaluation study of contemporary and prevalent VR locomotion techniques, examining the user experience (UX) they offer. First, the prevalent VR locomotion techniques are identified based on literature, i.e., walking-in-place, controller/joystick, and teleportation. Twenty-six adults are enrolled in the study and perform a game-like task using the techniques. The study follows a mixed methods approach, utilising the System Usability Scale survey, the Game Experience Questionnaire, and a semistructured interview to assess user experiences. Results indicate that the walking-in-place technique offers the highest immersion but also presents high levels of psychophysical discomfort. Controller/joystick VR locomotion is perceived as easy-to-use due to the users’ familiarity with controllers, whereas teleportation is considered to be effective due to its fast navigation, although its visual ‘jumps’ do break the users’ sense of immersion. Based on the interviews, the users focused on the following interaction dimensions to describe their VR locomotion experiences: (i) immersion and flow, (ii) ease-of-use and mastering, (iii) competence and sense of effectiveness, and (iv) psychophysical discomfort. The study implications for VR locomotion are discussed, along with the study limitations and the future direction for research.

EHR problem list clustering for improved topic-space navigation

BackgroundThe amount of patient-related information within clinical information systems accumulates over time, especially in cases where patients suffer from chronic diseases with many hospitalizations and consultations. The diagnosis or problem list is an important feature of the electronic health record, which provides a dynamic account of a patient’s current illness and past history. In the case of an Austrian hospital network, problem list entries are limited to fifty characters and are potentially linked to ICD-10. The requirement of producing ICD codes at each hospital stay, together with the length limitation of list items leads to highly redundant problem lists, which conflicts with the physicians’ need of getting a good overview of a patient in short time.This paper investigates a method, by which problem list items can be semantically grouped, in order to allow for fast navigation through patient-related topic spaces.MethodsWe applied a minimal language-dependent preprocessing strategy and mapped problem list entries as tf-idf weighted character 3-grams into a numerical vector space. Based on this representation we used the unweighted pair group method with arithmetic mean (UPGMA) clustering algorithm with cosine distances and inferred an optimal boundary in order to form semantically consistent topic spaces, taking into consideration different levels of dimensionality reduction via latent semantic analysis (LSA).ResultsWith the proposed clustering approach, evaluated via an intra- and inter-patient scenario in combination with a natural language pipeline, we achieved an average compression rate of 80% of the initial list items forming consistent semantic topic spaces with an F-measure greater than 0.80 in both cases. The average number of identified topics in the intra-patient case (μIntra = 78.4) was slightly lower than in the inter-patient case (μInter = 83.4). LSA-based feature space reduction had no significant positive performance impact in our investigations.ConclusionsThe investigation presented here is centered on a data-driven solution to the known problem of information overload, which causes ineffective human-computer interactions at clinicians’ work places. This problem is addressed by navigable disease topic spaces where related items are grouped and the topics can be more easily accessed.

Follow the Gap with Dynamic Window Approach

Follow the Gap Method (FGM) is an obstacle avoidance method which uses gap arrays. This method recursively directs the robot to the goal state while avoiding the obstacles through the safest gap. Since FGM is a geometric method, it does not consider the robot dynamics. For this reason, oscillations or collisions due to robot dynamics are possible. On the other hand, FGM calculates the desired heading angle, but it does not give linear and angular velocity reference. Dynamic Window Approach (DWA) is one of the most popular obstacle avoidance algorithms which does take robot dynamics into consideration. It calculates best angular and linear velocity pair which is chosen by an objective function. In this paper, an FGM-DW approach which uses the strongest elements of FGM and DWA methods to achieve safe, smooth and fast navigation is proposed. The FGM-DW approach provides these concerns and meets the low level angular and rotational velocity requirement of FGM. In this paper, the performance and analysis of FGM-DW are shown by both simulations and real-world experimental tests.

Motion planning and control of a planar polygonal linkage

For a polygonal linkage, we produce a fast navigation algorithm on its configuration space. The basic idea is to approximate M(L) by the vertex-edge graph of the cell decomposition of the configuration space discovered by the first author. The algorithm has three aspects: (1) the number of navigation steps does not exceed 15 (independent of the linkage), (2) each step is a disguised flex of a quadrilateral from one triangular configuration to another, which is a well understood type of flex, and (3) each step can be performed explicitly by adding some extra bars and obtaining a mechanism with one degree of freedom.

A multi-service data management platform for scientific oceanographic products

Abstract. An efficient, secure and interoperable data platform solution has been developed in the TESSA project to provide fast navigation and access to the data stored in the data archive, as well as a standard-based metadata management support. The platform mainly targets scientific users and the situational sea awareness high-level services such as the decision support systems (DSS). These datasets are accessible through the following three main components: the Data Access Service (DAS), the Metadata Service and the Complex Data Analysis Module (CDAM). The DAS allows access to data stored in the archive by providing interfaces for different protocols and services for downloading, variables selection, data subsetting or map generation. Metadata Service is the heart of the information system of the TESSA products and completes the overall infrastructure for data and metadata management. This component enables data search and discovery and addresses interoperability by exploiting widely adopted standards for geospatial data. Finally, the CDAM represents the back-end of the TESSA DSS by performing on-demand complex data analysis tasks.

Six-axis AFM in SEM with self-sensing and self-transduced cantilever for high speed analysis and nanolithography

Merging two state-of-the-art surface research techniques, in particular, atomic force microscopy (AFM) and scanning electron microscopy (SEM), within a single system is providing novel capabilities like direct visual feedback and life-monitoring of tip-induced nanoscale interactions. In addition, the combination of AFM and SEM accelerates nanoscale characterization and metrology development. Here, the concept and first results of a novel AFM-integration into a high resolution scanning electron microscope and focused ion beam system for nanoscale characterization is presented. In this context, a six-axis AFM system using self-sensing thermomechanically transduced active cantilever was developed and integrated. The design of the developed AFM-integration is described and its performance is demonstrated. Results from combined examinations applying fast AFM-methods and SEM-image fusion, AFM-SEM combined metrology verification, and three dimensional-visualization are shown. Simultaneous operation of SEM and AFM provides a fast navigation combined with sub-10 nm topographic image acquisition. Metrology application scenarios of combined studies are discussed, for example of MoS2 and diverse metrological test structures.

A priori knowledge-free fast positioning approach for BeiDou receivers

A Global Navigation Satellite System (GNSS) receiver usually needs a sufficient number of full pseudorange measurements to obtain a position solution. However, it is time-consuming to acquire full pseudorange information from only the satellite broadcast signals due to the navigation data features of GNSS. In order to realize fast positioning during a cold or warm start in a GNSS receiver, the existing approaches require an initial estimation of position and time or require a number of computational steps to recover the full pseudorange information from fractional pseudoranges and then compute the position solution. The BeiDou Navigation Satellite System (BDS) has a unique constellation distribution and a fast navigation data rate for geostationary earth orbit (GEO) satellites. Taking advantage of these features, we propose a fast positioning technique for BDS receivers. It simultaneously processes the full and fractional pseudorange measurements from the BDS GEOs and non-GEOs, respectively, which is faster than processing all full measurements. This method resolves the position solution and recovers the full pseudoranges for non-GEOs simultaneously within 1 s theoretically and does not need an estimate of the initial position. Simulation and real data experiments confirm that the proposed technique completes fast positioning without a priori position and time estimation, and the positioning accuracy is identical with the conventional single-point positioning approach using full pseudorange measurements from all available satellites.

Integrated genome browser: visual analytics platform for genomics.

Motivation: Genome browsers that support fast navigation through vast datasets and provide interactive visual analytics functions can help scientists achieve deeper insight into biological systems. Toward this end, we developed Integrated Genome Browser (IGB), a highly configurable, interactive and fast open source desktop genome browser.Results: Here we describe multiple updates to IGB, including all-new capabilities to display and interact with data from high-throughput sequencing experiments. To demonstrate, we describe example visualizations and analyses of datasets from RNA-Seq, ChIP-Seq and bisulfite sequencing experiments. Understanding results from genome-scale experiments requires viewing the data in the context of reference genome annotations and other related datasets. To facilitate this, we enhanced IGB’s ability to consume data from diverse sources, including Galaxy, Distributed Annotation and IGB-specific Quickload servers. To support future visualization needs as new genome-scale assays enter wide use, we transformed the IGB codebase into a modular, extensible platform for developers to create and deploy all-new visualizations of genomic data.Availability and implementation: IGB is open source and is freely available from http://bioviz.org/igb.Contact: aloraine@uncc.edu

SDHT for Fast Detection of Weak GNSS Signals

Successful and fast Global Navigation Satellite System (GNSS) positioning in indoor environments can enable many location based services (LBS). However, fast indoor GNSS positioning has been one of the biggest challenges for GNSS receivers due to the huge computational cost. To detect weak GNSS signals in indoor environments, a GNSS receiver should perform numerous correlations with a longer coherent integration interval for a denser Doppler frequency search, which is computationally too expensive. For a fast and low computational weak GNSS signal detection, we propose the synthesized Doppler frequency hypothesis testing (SDHT) technique that, utilizing the test results of only sparse Doppler frequency hypotheses, can estimate the test results of entire Doppler frequency hypotheses with small computations. We provide theoretical performance analysis of the proposed technique and demonstrate that the proposed technique reduces the computational cost for weak GNSS signal acquisition significantly and achieves faster signal acquisition than conventional techniques.

Online tracking of interventional devices for endovascular aortic repair.

The continuous integration of innovative imaging modalities into conventional vascular surgery rooms has led to an urgent need for computer assistance solutions that support the smooth integration of imaging within the surgical workflow. In particular, endovascular interventions performed under 2D fluoroscopic or angiographic imaging only, require reliable and fast navigation support for complex treatment procedures such as endovascular aortic repair. Despite the vast variety of image-based guide wire and catheter tracking methods, an adoption of these for detecting and tracking the stent graft delivery device is not possible due to its special geometry and intensity appearance. In this paper, we present, for the first time, the automatic detection and tracking of the stent graft delivery device in 2D fluoroscopic sequences on the fly. The proposed approach is based on the robust principal component analysis and extends the conventional batch processing towards an online tracking system that is able to detect and track medical devices on the fly. The proposed method has been tested on interventional sequences of four different clinical cases. In the lack of publicly available ground truth data, we have further initiated a crowd sourcing strategy that has resulted in 200 annotations by unexperienced users, 120 of which were used to establish a ground truth dataset for quantitatively evaluating our algorithm. In addition, we have performed a user study amongst our clinical partners for qualitative evaluation of the results. Although we calculated an average error in the range of nine pixels, the fact that our tracking method functions on the fly and is able to detect stent grafts in all unfolding stages without fine-tuning of parameters has convinced our clinical partners and they all agreed on the very high clinical relevance of our method.

Explanation in OLAP Data Cubes

OLAP is an important technology that offers a fast and interactive data navigation, it also provides tools to explore data cubes in order to extract interesting information from a multidimensional data structures. However, the OLAP exploration is done manually, without tools that could automatically extract relevant information from the cube. In addition OLAP is not capable of explaining relationships that could exist within data. This paper presents a new approach to coupling between data mining and online analytical processing. Its approach provides the explanation in OLAP data cubes by using the association rules between the inter-dimensional predicates. The mining process could be done by one of the two algorithms, Apriori and Fp-Growth, in which aggregate measures to calculate support and confidence are exploited. It also evaluates the interestingness of mined association rules according to the Lift criteria.

SU‐F‐BRD‐08: Guaranteed Epsilon‐Optimal Treatment Plans with Minimum Number of Beams for SBRT Using RayStation

Purpose:To efficiently find quality‐guaranteed treatment plans with the minimum number of beams for stereotactic body radiation therapy using RayStation.Methods:For a pre‐specified pool of candidate beams we use RayStation (a treatment planning software for clinical use) to identify the deliverable plan which uses all the beams with the minimum dose to organs at risk (OARs) and dose to the tumor and other structures in specified ranges. Then use the dose matrix information for the generated apertures from RayStation to solve a linear program to find the ideal plan with the same objective and constraints allowing use of all beams. Finally we solve a mixed integer programming formulation of the beam angle optimization problem (BAO) with the objective of minimizing the number of beams while remaining in a predetermined epsilon‐optimality of the ideal plan with respect to the dose to OARs. Since the treatment plan optimization is a multicriteria optimization problem, the planner can exploit the multicriteria optimization capability of RayStation to navigate the ideal dose distribution Pareto surface and select a plan of desired target coverage versus OARs sparing, and then use the proposed technique to reduce the number of beams while guaranteeing quality. For the numerical experiments two liver cases and one lung case with 33 non‐coplanar beams are considered.Results:The ideal plan uses an impractically large number of beams. The proposed technique reduces the number of beams to the range of practical application (5 to 9 beams) while remaining in the epsilon‐optimal range of 1% to 5% optimality gap.Conclusion:The proposed method can be integrated into a general algorithm for fast navigation of the ideal dose distribution Pareto surface and finding the treatment plan with the minimum number of beams, which corresponds to the delivery time, in epsilon‐optimality range of the desired ideal plan.The project was supported by the Federal Share of program income earned by Massachusetts General Hospital on C06 CA059267, Proton Therapy Research and Treatment Center and partially by RaySearch Laboratories.

Contextual Awareness in a WSN/RFID Fusion Navigation System

We present insight into how contextual awareness can be derived from, and improve, a fusion algorithm combing a WSN and a passive RFID for autonomous mobile robot navigation. Contextual awareness of not where the robot is, but rather the context in which it exists in relation to the environment and human user serves to improve accuracy in navigation, alters the speed of the robot, and modifies its behavior. The WSN system, using a virtual potential field, provides fast general navigation in open areas and the RFID provides precision navigation near static obstacles and in narrow areas. We verified the effectiveness of our approaches through navigational and guidance experiments.

A FAST AND ROBUST SCENE MATCHING METHOD FOR NAVIGATION

The selection of matching method is critical to the scene matching navigation system, as it determines the accuracy of navigation. A coarse-to-flne matching method, which combines the area-based and feature-based matching method, is presented to meet the requirements of navigation, including the real-time performance, the sub-pixel accuracy and the robustness. In the coarse matching stage, the real-time performance is achieved by a pyramid multi-resolution technique, and the robustness is improved by multi-scale circular template fusion. In the precise matching stage, an improved SIFT method is introduced to calculate the matching position and the rotation angle. To validate the method, some experiments are completed. The results show that the proposed method can achieve the sub-pixel matching accuracy and improve the angle accuracy to 0.1 - .

Compact representation of Web graphs with extended functionality

The representation of large subsets of the World Wide Web in the form of a directed graph has been extensively used to analyze structure, behavior, and evolution of those so-called Web graphs. However, interesting Web graphs are very large and their classical representations do not fit into the main memory of typical computers, whereas the required graph algorithms perform inefficiently on secondary memory. Compressed graph representations drastically reduce their space requirements while allowing their efficient navigation in compressed form. While the most basic navigation operation is to retrieve the successors of a node, several important Web graph algorithms require support for extended queries, such as finding the predecessors of a node, checking the presence of a link, or retrieving links between ranges of nodes. Those are seldom supported by compressed graph representations.This paper presents the k2-tree, a novel Web graph representation based on a compact tree structure that takes advantage of large empty areas of the adjacency matrix of the graph. The representation not only retrieves successors and predecessors in symmetric fashion, but also it is particularly efficient to check for specific links between nodes, or between ranges of nodes, or to list the links between ranges. Compared to the best representations in the literature supporting successor and predecessor queries, our technique offers the least space usage (1–3 bits per link) while supporting fast navigation to predecessors and successors (2–8μs per neighbor retrieved) and sharply outperforming the others on the extended queries. The representation is also of general interest and can be used to compress other kinds of graphs and data structures.

TH-A-116-08: Guaranteed Epsilon-Optimal Treatment Plans with Minimum Number of Beams for Stereotactic Body Radiation Therapy

Purpose: To efficiently find quality‐guaranteed treatment plans with the minimum number of beams for stereotactic body radiation therapy (SBRT). Methods: We formulate the beam angle optimization problem (BAO) as a mixed integer programming problem (MIP) whose solution gives the optimal beam orientation as well as optimal beam intensity. We first allow use of all candidate beams and find the ' 'ideal plan' ' with the objective of minimizing dose to organs at risk (OARs) while keeping the dose to the tumor and other structures in specified ranges. Then we resolve the MIP with the objective of minimizing the number of beams while remaining in a predetermined epsilon‐optimality of the ideal plan with respect to the dose to OARs. Since the treatment plan optimization is a multicriteria optimization problem, the planner can navigate the ideal dose distribution Pareto surface and select a plan of desired target coverage versus OARs sparing, and then use the proposed technique to reduce the number of beams while guaranteeing epsilon‐optimality. To reduce the computation time, we use a family of heuristic cuts, known as ((neighbor cuts)) while preserving epsilon‐optimality. For the numerical experiments a liver case with 34 and a lung case with 36 coplanar beams were considered. Results: The ideal plan uses an impractically large number of beams. The proposed technique reduced the number of beams to the range of practical application (5 to 9 beams) while remaining in the epsilon‐optimal range of 1% to 5% optimality gap. Adding the neighbor cuts reduced the computation time considerably. Conclusion: The proposed method can be integrated into a general algorithm for fast navigation of the ideal dose distribution Pareto surface and finding the treatment plan with the minimum number of beams, which corresponds to the delivery time, in epsilon‐optimality range of the desired ideal plan. The project was supported by the Federal Share of program income earned by Massachusetts; General Hospital on C06 CA059267, Proton Therapy Research and Treatment Center and also partially by RaySearch laboratories.

Wireless Sensor Network and RFID Fusion Approach for Mobile Robot Navigation

There are numerous applications for mobile robots that require relatively high levels of speed and precision. For many systems, these two properties are a tradeoff, as oftentimes increasing the movement speed can mean failing to detect some sensors. This research attempts to create a useful and practical system by combining a wireless sensor network with a passive radio frequency identification system. The sensor network provides fast general navigation in open areas and the radio frequency identification system provides precision navigation near static obstacles. By fusing the data from both systems, we are able to provide fast and accurate navigation for a mobile robot. Additionally, with WSN nodes and passive RFID tag mats, the system infrastructure can be easily installed in existing environments.

Autonomous terrain adaptation and user-friendly tele-operation of wheel-track hybrid mobile robot

This paper presents a terrain-adaptive wheel-track hybrid robot that uses a pair of combined wheel and track systems. The hybrid mobile platform can change the shape of track to adapt to various terrains so that it is able to move fast on flat terrain and to show good performance in overcoming stairs or obstacles. The proposed platform consists of an ordinary wheel structure for fast navigation on flat floors and a transformable tracked structure for climbing stairs effectively. In detail, three track arms installed on each side of the platform are used for the navigation mode transition between flatland navigation and stair climbing. The mode transition is determined and implemented by the adaptive driving mode control of the mobile robot. This wheel-track hybrid mobile platform is evaluated through experiments that assess its navigation performance in real and test-bed environments. This hybrid mobile robot is embodied to perform given tasks in a hazardous environment for surveillance, reconnaissance, and search and rescue applications.

Some remarks on GNSS integer ambiguity validation methods

Ambiguity resolution is an indispensable step in fast and high precision Global Navigation Satellite System (GNSS) based positioning. In general, ambiguity resolution consists of three steps. The first step is to estimate the ambiguities using a least-squares estimation process, from which the so called ‘float solution’ or real valued solution is obtained. Then in the second step, the float solution is used to search for the integer ambiguities. Once integer ambiguities are resolved, the last step is to apply the integer ambiguities into the models so that fairly accurate fixed solution can be generated. Owing to the importance of the integer ambiguities, one indispensable procedure that needs to be implemented in the second step is integer ambiguity validation. Over the past decades, considerable work has been concentrated on this procedure and various approaches have been proposed, such as R-ratio test, F-ratio test, W-ratio test, integer aperture estimator, etc. However, their performances are controversial. Therefore, in this contribution, an overview of the existing ambiguity validation methods is firstly presented, and then some numerical analysis is carried out to evaluate their performances.