4,781 research outputs found
An intelligent navigation system for an unmanned surface vehicle
Merged with duplicate record 10026.1/2768 on 27.03.2017 by CS (TIS)A multi-disciplinary research project has been carried out at the University of Plymouth to design
and develop an Unmanned Surface Vehicle (USV) named ýpringer. The work presented herein
relates to formulation of a robust, reliable, accurate and adaptable navigation system to enable
opringei to undertake various environmental monitoring tasks. Synergistically, sensor
mathematical modelling, fuzzy logic, Multi-Sensor Data Fusion (MSDF), Multi-Model Adaptive
Estimation (MMAE), fault adaptive data acquisition and an user interface system are combined to
enhance the robustness and fault tolerance of the onboard navigation system.
This thesis not only provides a holistic framework but also a concourse of computational
techniques in the design of a fault tolerant navigation system. One of the principle novelties of this
research is the use of various fuzzy logic based MSDF algorithms to provide an adaptive heading
angle under various fault situations for Springer. This algorithm adapts the process noise
covariance matrix ( Q) and measurement noise covariance matrix (R) in order to address one of
the disadvantages of Kalman filtering. This algorithm has been implemented in Spi-inger in real
time and results demonstrate excellent robustness qualities. In addition to the fuzzy logic based
MSDF, a unique MMAE algorithm has been proposed in order to provide an alternative approach
to enhance the fault tolerance of the heading angles for Springer.
To the author's knowledge, the work presented in this thesis suggests a novel way forward in the
development of autonomous navigation system design and, therefore, it is considered that the work
constitutes a contribution to knowledge in this area of study. Also, there are a number of ways in
which the work presented in this thesis can be extended to many other challenging domains.DEVONPORT MANAGEMENT LTD, J&S MARINE LTD
AND
SOUTH WEST WATER PL
A Review of Indoor Millimeter Wave Device-based Localization and Device-free Sensing Technologies and Applications
The commercial availability of low-cost millimeter wave (mmWave)
communication and radar devices is starting to improve the penetration of such
technologies in consumer markets, paving the way for large-scale and dense
deployments in fifth-generation (5G)-and-beyond as well as 6G networks. At the
same time, pervasive mmWave access will enable device localization and
device-free sensing with unprecedented accuracy, especially with respect to
sub-6 GHz commercial-grade devices. This paper surveys the state of the art in
device-based localization and device-free sensing using mmWave communication
and radar devices, with a focus on indoor deployments. We first overview key
concepts about mmWave signal propagation and system design. Then, we provide a
detailed account of approaches and algorithms for localization and sensing
enabled by mmWaves. We consider several dimensions in our analysis, including
the main objectives, techniques, and performance of each work, whether each
research reached some degree of implementation, and which hardware platforms
were used for this purpose. We conclude by discussing that better algorithms
for consumer-grade devices, data fusion methods for dense deployments, as well
as an educated application of machine learning methods are promising, relevant
and timely research directions.Comment: 43 pages, 13 figures. Accepted in IEEE Communications Surveys &
Tutorials (IEEE COMST
Large-scale phenomena, chapter 3, part D
Oceanic phenomena with horizontal scales from approximately 100 km up to the widths of the oceans themselves are examined. Data include: shape of geoid, quasi-stationary anomalies due to spatial variations in sea density and steady current systems, and the time dependent variations due to tidal and meteorological forces and to varying currents
The design of an autonomous maritime navigation system for unmanned surface vehicles
This paper presents the development of an autonomous maritime navigation system for unmanned
surface vehicles (USVs). In the autonomous system various maritime navigational devices are
connected to obtain necessary navigational information but with uncertainties. To improve signal
accuracy as well as robustness, a novel multi-sensor data fusion algorithm is proposed and
developed. Then, a new predictive path planning algorithm is employed to provide an advisory
collision-free trajectory. Practical trials and computer based simulations are carried out to prove the
effectiveness of the developed syste
NASA SBIR abstracts of 1991 phase 1 projects
The objectives of 301 projects placed under contract by the Small Business Innovation Research (SBIR) program of the National Aeronautics and Space Administration (NASA) are described. These projects were selected competitively from among proposals submitted to NASA in response to the 1991 SBIR Program Solicitation. The basic document consists of edited, non-proprietary abstracts of the winning proposals submitted by small businesses. The abstracts are presented under the 15 technical topics within which Phase 1 proposals were solicited. Each project was assigned a sequential identifying number from 001 to 301, in order of its appearance in the body of the report. Appendixes to provide additional information about the SBIR program and permit cross-reference of the 1991 Phase 1 projects by company name, location by state, principal investigator, NASA Field Center responsible for management of each project, and NASA contract number are included
Numerical Fitting-based Likelihood Calculation to Speed up the Particle Filter
The likelihood calculation of a vast number of particles is the computational
bottleneck for the particle filter in applications where the observation
information is rich. For fast computing the likelihood of particles, a
numerical fitting approach is proposed to construct the Likelihood Probability
Density Function (Li-PDF) by using a comparably small number of so-called
fulcrums. The likelihood of particles is thereby analytically inferred,
explicitly or implicitly, based on the Li-PDF instead of directly computed by
utilizing the observation, which can significantly reduce the computation and
enables real time filtering. The proposed approach guarantees the estimation
quality when an appropriate fitting function and properly distributed fulcrums
are used. The details for construction of the fitting function and fulcrums are
addressed respectively in detail. In particular, to deal with multivariate
fitting, the nonparametric kernel density estimator is presented which is
flexible and convenient for implicit Li-PDF implementation. Simulation
comparison with a variety of existing approaches on a benchmark 1-dimensional
model and multi-dimensional robot localization and visual tracking demonstrate
the validity of our approach.Comment: 42 pages, 17 figures, 4 tables and 1 appendix. This paper is a
draft/preprint of one paper submitted to the IEEE Transaction
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