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Triple GPS Localization
The purpose of this thesis is to increase the positional accuracy of Global Position System (GPS) modules using an artificial intelligence algorithm. Three basic and identical GPS modules were setup in an equilateral triangle formation with side lengths of one meter. The triangle was placed in four separate locations where approximately 700 GPS data points were collected per GPS module. The data was then analyzed and tested using a Gaussian distribution. In the best-case scenario, the Triple GPS Localization algorithm was able to improve the localization accuracy by 82%. This shows that utilizing a machine-learning algorithm can improve the positional accuracy of any GPS module
Increasing the Efficiency of 6-DoF Visual Localization Using Multi-Modal Sensory Data
Localization is a key requirement for mobile robot autonomy and human-robot
interaction. Vision-based localization is accurate and flexible, however, it
incurs a high computational burden which limits its application on many
resource-constrained platforms. In this paper, we address the problem of
performing real-time localization in large-scale 3D point cloud maps of
ever-growing size. While most systems using multi-modal information reduce
localization time by employing side-channel information in a coarse manner (eg.
WiFi for a rough prior position estimate), we propose to inter-weave the map
with rich sensory data. This multi-modal approach achieves two key goals
simultaneously. First, it enables us to harness additional sensory data to
localise against a map covering a vast area in real-time; and secondly, it also
allows us to roughly localise devices which are not equipped with a camera. The
key to our approach is a localization policy based on a sequential Monte Carlo
estimator. The localiser uses this policy to attempt point-matching only in
nodes where it is likely to succeed, significantly increasing the efficiency of
the localization process. The proposed multi-modal localization system is
evaluated extensively in a large museum building. The results show that our
multi-modal approach not only increases the localization accuracy but
significantly reduces computational time.Comment: Presented at IEEE-RAS International Conference on Humanoid Robots
(Humanoids) 201
Cramer-Rao Bounds for Joint RSS/DoA-Based Primary-User Localization in Cognitive Radio Networks
Knowledge about the location of licensed primary-users (PU) could enable
several key features in cognitive radio (CR) networks including improved
spatio-temporal sensing, intelligent location-aware routing, as well as aiding
spectrum policy enforcement. In this paper we consider the achievable accuracy
of PU localization algorithms that jointly utilize received-signal-strength
(RSS) and direction-of-arrival (DoA) measurements by evaluating the Cramer-Rao
Bound (CRB). Previous works evaluate the CRB for RSS-only and DoA-only
localization algorithms separately and assume DoA estimation error variance is
a fixed constant or rather independent of RSS. We derive the CRB for joint
RSS/DoA-based PU localization algorithms based on the mathematical model of DoA
estimation error variance as a function of RSS, for a given CR placement. The
bound is compared with practical localization algorithms and the impact of
several key parameters, such as number of nodes, number of antennas and
samples, channel shadowing variance and correlation distance, on the achievable
accuracy are thoroughly analyzed and discussed. We also derive the closed-form
asymptotic CRB for uniform random CR placement, and perform theoretical and
numerical studies on the required number of CRs such that the asymptotic CRB
tightly approximates the numerical integration of the CRB for a given
placement.Comment: 20 pages, 11 figures, 1 table, submitted to IEEE Transactions on
Wireless Communication
Subjective evaluation of an emerging theory of low-frequency sound source localization in closed acoustic spaces
An earlier reported theory of low-frequency sound-source localization within closed acoustic spaces proposed that virtual image acuity is strongly dependent on sufficient inter-arrival time between a direct sound and its first reflection. This current study aims to test the theory’s predictions by subjective experiment where participants are required to indicate perceived sound source direction, but without knowledge of loudspeaker location. Test signals of frequencies 40 Hz to 115 Hz take the form of either windowed sine or square waves. Results confirm broad agreement with theoretical expectations and support the conjecture, contrary to common expectation, that low-frequency sound localization within the context of closed acoustic spaces is possible, although strongly dependent on system configuration and size of a listening space
A New Vehicle Localization Scheme Based on Combined Optical Camera Communication and Photogrammetry
The demand for autonomous vehicles is increasing gradually owing to their
enormous potential benefits. However, several challenges, such as vehicle
localization, are involved in the development of autonomous vehicles. A simple
and secure algorithm for vehicle positioning is proposed herein without
massively modifying the existing transportation infrastructure. For vehicle
localization, vehicles on the road are classified into two categories: host
vehicles (HVs) are the ones used to estimate other vehicles' positions and
forwarding vehicles (FVs) are the ones that move in front of the HVs. The FV
transmits modulated data from the tail (or back) light, and the camera of the
HV receives that signal using optical camera communication (OCC). In addition,
the streetlight (SL) data are considered to ensure the position accuracy of the
HV. Determining the HV position minimizes the relative position variation
between the HV and FV. Using photogrammetry, the distance between FV or SL and
the camera of the HV is calculated by measuring the occupied image area on the
image sensor. Comparing the change in distance between HV and SLs with the
change in distance between HV and FV, the positions of FVs are determined. The
performance of the proposed technique is analyzed, and the results indicate a
significant improvement in performance. The experimental distance measurement
validated the feasibility of the proposed scheme
Development of a tabletop guidance system for educational robots
The guidance of a vehicle in an outdoor setting is typically implemented using a Real Time Kinematic Global Positioning System (RTK-GPS) potentially enhanced by auxiliary sensors such as electronic compasses, rotation encoders, gyroscopes, and vision systems. Since GPS does not function in an indoor setting where educational competitions are often held, an alternative guidance system was developed. This article describes a guidance method that contains a laser-based localization system, which uses a robot-borne single laser transmitter spinning in a horizontal plane at an angular velocity up to 81 radians per second. Sensor arrays positioned in the corners of a flat rectangular table with dimensions of 1.22 m × 1.83 m detected the laser beam passages. The relative time differences among the detections of the laser passages gave an indication of the angles of the sensors with respect to the laser beam transmitter on the robot. These angles were translated into Cartesian coordinates. The guidance of the robot was implemented using a uni-directional wireless serial connection and position feedback from the localization system. Three experiments were conducted to test the system: 1) the accuracy of the static localization system was determined while the robot stood still. In this test the average error among valid measurements was smaller than 0.3 %. However, a maximum of 3.7 % of the measurements were invalid due to several causes. 2) The accuracy of the guidance system was assessed while the robot followed a straight line. The average deviation from this straight line was 3.6 mm while the robot followed a path with a length of approximately 0.9 m. 3) The overall performance of the guidance system was studied while the robot followed a complex path consisting of 33 sub-paths. The conclusion was that the system worked reasonably accurate, unless the robot came in close proximity
High precision real-time location estimates in a real-life barn environment using a commercial ultra wideband chip
Structural changes lead to an increase in the number of dairy cows and dry sows kept per group. This has consequences in how easily a farmer can supervise his herd and may be detrimental to animal welfare, specifically regarding social relations, time budget and area of residence. An automated tracking system can support the farmer in his management activities and can provide the foundation for a scientific assessment of the welfare consequences of large groups. In this study, a relatively simple and inexpensive real time location system (RTLS) was developed with the aim of achieving precise localization of several tags (animals) in real time and in a real barn environment. The RTLS was based on the ultra-wideband (UWB) technology provided by DecaWave and was adapted for a time difference of arrival (TDoA) procedure to estimate the tags’ positions. The RTLS can handle up to a hundred tags simultaneously using a Pure ALOHA random access method at 1-second intervals. The localization of the tags was estimated in 2D on a given fixed height using a constrained Gauss-Newton algorithm to increase accuracy and stability. The performance of the overall system was evaluated in two different dairy barns. To determine the precision of the system, static and dynamic positions measured at withers height of a cow (1.5 m) and closer to the ground mimicking a lying cow were compared with a reference system (theodolite). The 2D deviations between the systems were used as a measure of precision. In addition, the scalability in respect to the number of tags and the size of the observed area was examined in situations with ten tags and the situation with 100 tags was simulated with a ten-fold increase in sampling rate.
According to the field test, the system as developed can be used for the individual localization of animals. At withers height, most of the measured locations deviated less than 0.5 m from the localizations as measured by the theodolite. At lower heights, and closer to the corners of the observed area, some localization estimates were somewhat larger. This was also the case close to large metal barn infrastructure. The measured collision rate of 11% for 100 tags was low. In spite of its low price, the system as a whole is therefore promising and ready for a next step, which should include the observation of large groups of real animals on working farms
Hybrid 3D Localization for Visible Light Communication Systems
In this study, we investigate hybrid utilization of angle-of-arrival (AOA)
and received signal strength (RSS) information in visible light communication
(VLC) systems for 3D localization. We show that AOA-based localization method
allows the receiver to locate itself via a least squares estimator by
exploiting the directionality of light-emitting diodes (LEDs). We then prove
that when the RSS information is taken into account, the positioning accuracy
of AOA-based localization can be improved further using a weighted least
squares solution. On the other hand, when the radiation patterns of LEDs are
explicitly considered in the estimation, RSS-based localization yields highly
accurate results. In order to deal with the system of nonlinear equations for
RSS-based localization, we develop an analytical learning rule based on the
Newton-Raphson method. The non-convex structure is addressed by initializing
the learning rule based on 1) location estimates, and 2) a newly developed
method, which we refer as random report and cluster algorithm. As a benchmark,
we also derive analytical expression of the Cramer-Rao lower bound (CRLB) for
RSS-based localization, which captures any deployment scenario positioning in
3D geometry. Finally, we demonstrate the effectiveness of the proposed
solutions for a wide range of LED characteristics and orientations through
extensive computer simulations.Comment: Submitted to IEEE/OSA Journal of Lightwave Technology (10 pages, 14
figures
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