Search results for "Sensor fusion"
showing 10 items of 64 documents
Asynchronous sensor fusion of GPS, IMU and CAN-based odometry for heavy-duty vehicles
2021
[EN] In heavy-duty vehicles, multiple signals are available to estimate the vehicle's kinematics, such as Inertial Measurement Unit (IMU), Global Positioning System (GPS) and linear and angular speed readings from wheel tachometers on the internal Controller Area Network (CAN). These signals have different noise variance, bandwidth and sampling rate (being the latter, possibly, irregular). In this paper we present a non-linear sensor fusion algorithm allowing asynchronous sampling and non-causal smoothing. It is applied to achieve accuracy improvements when incorporating odometry measurements from CAN bus to standard GPS+IMU kinematic estimation, as well as the robustness against missing da…
A comparison of STARFM and an unmixing-based algorithm for Landsat and MODIS data fusion
2015
article i nfo The focus of the current study is to compare data fusion methods applied to sensors with medium- and high- spatial resolutions. Two documented methods are applied, the spatial and temporal adaptive reflectance fusion model (STARFM) and an unmixing-based method which proposes a Bayesian formulation to incorporate prior spectral information.Furthermore, thestrengths of both algorithms arecombined ina novel data fusionmethod: the Spatial and Temporal Reflectance Unmixing Model (STRUM). The potential of each method is demonstrated using simulation imagery and Landsat and MODIS imagery. The theoretical basis of the algorithms causes STARFM and STRUM to produce Landsat-like reflecta…
Restoration and Enhancement of Historical Stereo Photos Through Optical Flow
2021
Restoration of digital visual media acquired from repositories of historical photographic and cinematographic material is of key importance for the preservation, study and transmission of the legacy of past cultures to the coming generations. In this paper, a fully automatic approach to the digital restoration of historical stereo photographs is proposed. The approach exploits the content redundancy in stereo pairs for detecting and fixing scratches, dust, dirt spots and many other defects in the original images, as well as improving contrast and illumination. This is done by estimating the optical flow between the images, and using it to register one view onto the other both geometrically …
Sensor Fusion Localization and Navigation for Visually Impaired People
2018
In this paper, we present an innovative cyber physical system for indoor and outdoor localization and navigation, based on the joint utilization of dead-reckoning and computer vision techniques on a smartphone-centric tracking system. The system is explicitly designed for visually impaired people, but it can be easily generalized to other users, and it is built under the assumption that special reference signals, such as colored tapes, painted lines, or tactile paving, are deployed in the environment for guiding visually impaired users along pre-defined paths. Differently from previous works on localization, which are focused only on the utilization of inertial sensors integrated into the s…
<title>Methodology for quantitative analysis of scaling effects in multiresolution datasets acquired with airborne sensors flying at different …
2001
Scaling issues are always playing a critical role in most studies based on remote sensing data. The process of getting quantitative scaling information from raw multi-resolution images is not trivial, and many aspects must be taken very carefully into consideration. To get a better picture about the role of spatial resolution, we conducted a series of flights in summer 1997, in several test sites over Spain and Portugal. In order to minimize the time of acquisition (to get minimal changes in atmospheric status and solar illumination) we used three flight altitude levels, that produced images with 1.25 m, 3 m and 12 m resolutions. The main steps in our methodology are: a) Geometrical registr…
Analysis of multi-source metabolomic data using joint and individual variation explained (JIVE).
2015
Metabolic profiling is increasingly being used for understanding biological processes but there is no single analytical technique that provides a complete quantitative or qualitative profiling of the metabolome. Data fusion (i.e. joint analysis of data from multiple sources) has the potential to circumvent this issue facilitating knowledge discovery and reliable biomarker identification. Another field of application of data fusion is the simultaneous analysis of metabolomic changes through several biofluids or tissues. However, metabolomics typically deals with large datasets, with hundreds to thousands of variables and the identification of shared and individual factors or structures acros…
A decision support system based on multisensor data fusion for sustainable greenhouse management
2018
The sustainable exploitation of natural resources is nowadays an important challenge for governments and institutions, considering the expected increase of the world population. In order to respond to this emergent criticality, the principles of green economy have been introduced in the European policy discussion to achieve a good compromise between the sustainability and the profitability of productions by increasing the efficiency of farming operations. Such approach poses some technical and financial challenges for small-sized enterprises because they generally do not possess adequate internal knowledge, nor they can acquire external expertise due to their budget restrictions. Decision S…
Autoencoders and Data Fusion Based Hybrid Health Indicator for Detecting Bearing and Stator Winding Faults in Electric Motors
2018
The main objective of a condition monitoring programs is to track the health status of critical components of a machine. In this paper, a hybrid health indicator is proposed to monitor the health status of bearings and stator winding of a motor. The proposed method is based on a feature learning from deep autoencoders and data fusion. The features can be learned by autoencoders using individual current and vibration signals, and then learning features are fused to make final health indicators. The experimental data from a permanent magnet synchronous motor is used to validate the proposed method. Promising results in detecting faults and severities of the stator and bearing faults at differ…
Tracking Mobile Robot in Indoor Wireless Sensor Networks
2014
Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://10.1155/2014/837050 This work addresses the problem of tracking mobile robots in indoor wireless sensor networks (WSNs). Our approach is based on a localization scheme with RSSI (received signal strength indication) which is used widely in WSN. The developed tracking system is designed for continuous estimation of the robot's trajectory. A WSN, which is composed of many very simple and cheap wireless sensor nodes, is deployed at a specific region of interest. The wireless sensor nodes collect RSSI information sent by mobile robots. A range-based data fusion sche…
Increasing the accuracy of untaught robot positions by means of a multi-camera system
2010
We aim to improve the absolute in line positional accuracy of a robot-guided effector to better than 1 mm. We do so using photogrammetric techniques and by relying heavily on simulations to fine tune each parameter and avoid weak configurations. We also use simulations to design an LED calibration object adapted to this application. A test procedure enables us to validate both the simulated results as well as the calibration procedure. The test results exceed expectations by improving the absolute positioning of a robot effector by a factor of 20.