A Low-Cost, High Rate Motion Software Sensor System Based on Novel Data Fusion for Unmanned Surface Vehicle Navigation and Oceanographic Instrumentation Motion Correction

2011 ◽  
Author(s):  
Chrystel R. Gelin ◽  
Nikolaos I. Xiros
Keyword(s):  
Data Fusion ◽  
Low Cost ◽  
Underwater Vehicles ◽  
High Rate ◽  
Measurement Unit ◽  
Vehicle Navigation ◽  
Gps Receiver ◽  
Unmanned Surface Vehicle ◽  
Flux Gate ◽  
Tilt Sensor

One of the major challenges in the navigation of underwater vehicles is obtaining precise and reliable positioning updates. Dead-Reckoning aided with Doppler velocity measurement has been, and remains, the most common method for underwater navigation for small vehicles. DR uses a set of navigation instruments to estimate the position of the vehicle by integrating the body-fixed velocity, accelerations, and angular rates with respect to time. Instrument error and bias lead to position error that increases exponentially with time. Thus, current DR systems require frequent position recalibrations. The Global Positioning System (GPS) provides measurements of geodetic coordinates for air and surface vehicles and it is often used to correct positioning error. However, underwater vehicles cannot use GPS for inflight navigation because GPS signals only penetrate a few centimeters past the air-sea interface. Thus, underwater vehicle navigation systems are limited to periodic position update from the GPS when they surface and extend an antenna through the air-sea interface. Standard GPS receivers are unable to provide the rate or precision required when used on a small vessel such as an Unmanned Surface Vehicle (USV). To overcome this, a low cost high rate motion measurement system for an USV with underwater and oceanographic purposes is proposed. The proposed onboard system for the USV consists of an Inertial Measurement Unit (IMU) with accelerometers and rate gyros, a GPS receiver, a flux-gate compass, a roll and tilt sensor and an ADCP. Interfacing all the sensors proved rather challenging because of their different characteristics. Some of the instruments have digital output (Compass/ADCP/GPS) while others have an analog output (IMU/tilt sensor). The proposed data fusion technique integrates the IMU, GPS receiver, flux-gate compass as well as tilt sensor and develops an embeddable software package, using real time data fusion methods, for a USV to aid in navigation and control as well as controlling an onboard Acoustic Doppler Current Profiler (ADCP). While ADCPs non-intrusively measure water flow, they suffer from the inability to distinguish between motions in the water column and self-motion. Thus, the vessel motion contamination needs to be removed to analyze the data and the system developed in this text provides the motion measurements and processing to accomplish this task.

Maximum Correntropy Kalman Filter for Orientation Estimation With Application to LiDAR Inertial Odometry

2020 ◽  
Author(s):  
Seyed Fakoorian ◽  
Matteo Palieri ◽  
Angel Santamaria-Navarro ◽  
Cataldo Guaragnella ◽  
Dan Simon ◽  
...  
Keyword(s):  
Kalman Filtering ◽  
Inertial Measurement Unit ◽  
Low Cost ◽  
Attitude Estimation ◽  
High Rate ◽  
Measurement Unit ◽  
Orientation Estimation ◽  
Localization Accuracy ◽  
Inertial Measurement ◽  
Robotic Applications

Abstract Accurate attitude estimation using low-cost sensors is an important capability to enable many robotic applications. In this paper, we present a method based on the concept of correntropy in Kalman filtering to estimate the 3D orientation of a rigid body using a low-cost inertial measurement unit (IMU). We then leverage the proposed attitude estimation framework to develop a LiDAR-Intertial Odometry (LIO) demonstrating improved localization accuracy with respect to traditional methods. This is of particular importance when the robot undergoes high-rate motions that typically exacerbate the issues associated with low-cost sensors. The proposed orientation estimation approach is first validated using the data coming from a low-cost IMU sensor. We further demonstrate the performance of the proposed LIO solution in a simulated robotic cave exploration scenario.

scholarly journals A low-cost IMU/GPS position accuracy experimental study using extended kalman filter data fusion in real environments

2021 ◽  
Vol 297 ◽  
pp. 01040
Author(s):  
Aziz El Fatimi ◽  
Adnane Addaim ◽  
Zouhair Guennoun
Keyword(s):  
Experimental Study ◽  
Data Fusion ◽  
Low Cost ◽  
Three Dimensional ◽  
Measurement Unit ◽  
Circular Path ◽  
Positioning System ◽  
Fusion Algorithm ◽  
Position Accuracy ◽  
The Stability

In a three-dimensional environment, the navigation of a vehicle in airspace, terrestrial space, or maritime space presents complex aspects concerning the determination of its position, its orientation, and the stability of the processing of the asynchronous data coming from the various sensors during navigation. In this context, this paper presents an experimental analysis of the position accuracy estimated by a low-cost inertial measurement unit coupled, by the extended Kalman data fusion algorithm, with a system of absolute measurements of a positioning system received from a GPS which designates the global positioning system. The different scenarios of the experimental study carried out during this work concerned three tests in a real environment, such as the navigation in a course inside the city of Rabat/Morocco with a moderate speed, a section on the highway at a speed of 120 Km/h and a circular path around a roundabout. The experimental results proved that the low-cost sensors studied are a good candidate for civil navigation applications.

scholarly journals AQUALOC: An underwater dataset for visual–inertial–pressure localization

2019 ◽  
Vol 38 (14) ◽  
pp. 1549-1559 ◽  
Author(s):  
Maxime Ferrera ◽  
Vincent Creuze ◽  
Julien Moras ◽  
Pauline Trouvé-Peloux
Keyword(s):  
Inertial Measurement Unit ◽  
Low Cost ◽  
Underwater Vehicles ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Computing Unit ◽  
Underwater Environment ◽  
Localization And Mapping ◽  
Vision Based Localization ◽  
Archeological Site

We present a new dataset, dedicated to the development of simultaneous localization and mapping methods for underwater vehicles navigating close to the seabed. The data sequences composing this dataset are recorded in three different environments: a harbor at a depth of a few meters, a first archeological site at a depth of 270 meters, and a second site at a depth of 380 meters. The data acquisition is performed using remotely operated vehicles equipped with a monocular monochromatic camera, a low-cost inertial measurement unit, a pressure sensor, and a computing unit, all embedded in a single enclosure. The sensors’ measurements are recorded synchronously on the computing unit and 17 sequences have been created from all the acquired data. These sequences are made available in the form of ROS bags and as raw data. For each sequence, a trajectory has also been computed offline using a structure-from-motion library in order to allow the comparison with real-time localization methods. With the release of this dataset, we wish to provide data difficult to acquire and to encourage the development of vision-based localization methods dedicated to the underwater environment. The dataset can be downloaded from: http://www.lirmm.fr/aqualoc/

scholarly journals Terrain Analytics for Precision Agriculture with Automated Vehicle Sensors and Data Fusion

2021 ◽  
Vol 13 (5) ◽  
pp. 2905
Author(s):  
Wei Zhao ◽  
Tianxin Li ◽  
Bozhao Qi ◽  
Qifan Nie ◽  
Troy Runge
Keyword(s):  
Data Fusion ◽  
Precision Agriculture ◽  
Low Cost ◽  
Measurement Unit ◽  
Nutrient Runoff ◽  
Automated Vehicle ◽  
Terrain Attributes ◽  
Simulated Environments ◽  
Set Up ◽  
Vehicle Sensors

Precision agriculture aims to use minimal inputs to generate maximal yields by managing the plant and its environment at a discrete instead of a field level. This new farming methodology requires localized field data including topological terrain attributes, which influence irrigation, field moisture, nutrient runoff, soil compaction, and traction and stability for traversing agriculture machines. Existing research studies have used different sensors, such as distance sensors and cameras, to collect topological information, which may be constrained by energy cost, performance, price, etc. This study proposed a low-cost method to perform farmland topological analytics using sensor implementation and data processing. Inertial measurement unit sensors, which are widely used in automated vehicle study, and a camera are set up on a robot vehicle. Then experiments are conducted under indoor simulated environments that include five common topographies that would be encountered on farms, combined with validation experiments in a real-world field. A data fusion approach was developed and implemented to track robot vehicle movements, monitor the surrounding environment, and finally recognize the topography type in real time. The resulting method was able to clearly recognize topography changes. This low-cost and easy-mount method will be able to augment and calibrate existing mapping algorithms with multidimensional information. Practically, it can also achieve immediate improvement for the operation and path planning of large agricultural machines.

Moxifloxacin Based Triple Therapy as Alternative to Standard Therapy in Helicobacter Pylori Eradication.

2020 ◽  
Vol 18 ◽  
Author(s):  
Mohammed Hussien Ahmed ◽  
Sherief Abd-Elsalam ◽  
Aya Mohammed Mahrous
Keyword(s):  
Helicobacter Pylori ◽  
Triple Therapy ◽  
Therapy Group ◽  
Low Cost ◽  
High Rate ◽  
Helicobacter Pylori Eradication ◽  
Treatment Regimens ◽  
Group A ◽  
H Pylori ◽  
Group B

Introduction: Helicobacter pylori eradication remains a problematic issue. We are in an urgent need for finding a treatment regimen that achieves eradication at a low cost and less side effect. Recent published results showing a high rate of resistance and with clarithromycin-based treatment regimens. The aim of the study was to compare moxifloxacin therapy and classic clarithromycin triple therapy in H. pylori eradication. Methods: This was a pilot study that enrolled 60 patients with helicobacter pylori associated gastritis. Diagnosis was done by assessment of H. pylori Ag in the stool. The patients were randomly assigned to receive either moxifloxacin based therapy (Group A), or clarithromycin based therapy (Group B) for two weeks. We stopped the treatment for another two weeks then reevaluation for cure was done. Results: 90 % of patients had negative H. pylori Ag in the stool after 2 weeks of stoppage of the treatment in group A versus 66.7 % in Group B. None of the patients in both groups had major side effects. Conclusion: Moxifloxacin-based therapy showed higher eradication power and less resistance when compared to clarithromycin triple therapy.

scholarly journals Biomechanics of Trail Running Performance: Quantification of Spatio-Temporal Parameters by Using Low Cost Sensors in Ecological Conditions

2021 ◽  
Vol 11 (5) ◽  
pp. 2093
Author(s):  
Noé Perrotin ◽  
Nicolas Gardan ◽  
Arnaud Lesprillier ◽  
Clément Le Goff ◽  
Jean-Marc Seigneur ◽  
...  
Keyword(s):  
Heart Rate ◽  
Low Cost ◽  
Step Length ◽  
Measurement Unit ◽  
Ecological Conditions ◽  
Sports Science ◽  
Ground Contact Time ◽  
Spatio Temporal ◽  
Performance Results ◽  
Trail Running

The recent popularity of trail running and the use of portable sensors capable of measuring many performance results have led to the growth of new fields in sports science experimentation. Trail running is a challenging sport; it usually involves running uphill, which is physically demanding and therefore requires adaptation to the running style. The main objectives of this study were initially to use three “low-cost” sensors. These low-cost sensors can be acquired by most sports practitioners or trainers. In the second step, measurements were taken in ecological conditions orderly to expose the runners to a real trail course. Furthermore, to combine the collected data to analyze the most efficient running techniques according to the typology of the terrain were taken, as well on the whole trail circuit of less than 10km. The three sensors used were (i) a Stryd sensor (Stryd Inc. Boulder CO, USA) based on an inertial measurement unit (IMU), 6 axes (3-axis gyroscope, 3-axis accelerometer) fixed on the top of the runner’s shoe, (ii) a Global Positioning System (GPS) watch and (iii) a heart belt. Twenty-eight trail runners (25 men, 3 women: average age 36 ± 8 years; height: 175.4 ± 7.2 cm; weight: 68.7 ± 8.7 kg) of different levels completed in a single race over a 8.5 km course with 490 m of positive elevation gain. This was performed with different types of terrain uphill (UH), downhill (DH), and road sections (R) at their competitive race pace. On these sections of the course, cadence (SF), step length (SL), ground contact time (GCT), flight time (FT), vertical oscillation (VO), leg stiffness (Kleg), and power (P) were measured with the Stryd. Heart rate, speed, ascent, and descent speed were measured by the heart rate belt and the GPS watch. This study showed that on a ≤10 km trail course the criteria for obtaining a better time on the loop, determined in the test, was consistency in the effort. In a high percentage of climbs (>30%), two running techniques stand out: (i) maintaining a high SF and a short SL and (ii) decreasing the SF but increasing the SL. In addition, it has been shown that in steep (>28%) and technical descents, the average SF of the runners was higher. This happened when their SL was shorter in lower steep and technically challenging descents.

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