scholarly journals Performance Evaluation of Autonomous Driving Control Algorithm for a Crawler-Type Agricultural Vehicle Based on Low-Cost Multi-Sensor Fusion Positioning

2020 ◽  
Vol 10 (13) ◽  
pp. 4667 ◽  
Author(s):  
Joong-hee Han ◽  
Chi-ho Park ◽  
Jay Hyoun Kwon ◽  
Jisun Lee ◽  
Tae Soo Kim ◽  
...  
Keyword(s):  
Control Algorithm ◽  
Low Cost ◽  
Autonomous Driving ◽  
Maximum Error ◽  
Sensor Technology ◽  
Motion Sensor ◽  
Integration Algorithm ◽  
Sensor Module ◽  
Agricultural Vehicle ◽  
Mean Square Errors

The agriculture sector is currently facing the problems of aging and decreasing skilled labor, meaning that the future direction of agriculture will be a transition to automation and mechanization that can maximize efficiency and decrease costs. Moreover, interest in the development of autonomous agricultural vehicles is increasing due to advances in sensor technology and information and communication technology (ICT). Therefore, an autonomous driving control algorithm using a low-cost global navigation satellite system (GNSS)-real-time kinematic (RTK) module and a low-cost motion sensor module was developed to commercialize an autonomous driving system for a crawler-type agricultural vehicle. Moreover, an autonomous driving control algorithm, including the GNSS-RTK/motion sensor integration algorithm and the path-tracking control algorithm, was proposed. Then, the performance of the proposed algorithm was evaluated based on three trajectories. The Root Mean Square Errors (RMSEs) of the path-following of each trajectory are calculated to be 9, 7, and 7 cm, respectively, and the maximum error is smaller than 30 cm. Thus, it is expected that the proposed algorithm could be used to conduct autonomous driving with about a 10 cm-level of accuracy.

Simultaneous Calibration for MEMS Gyroscopes of the Rocket IMU

2014 ◽  
Vol 896 ◽  
pp. 656-659 ◽  
Author(s):  
Wahyudi ◽  
Adhi Susanto ◽  
Wahyu Widada ◽  
Sasongko P. Hadi
Keyword(s):  
Low Cost ◽  
Angular Rate ◽  
Calibration Method ◽  
Sensor Technology ◽  
Measurement Unit ◽  
Angular Rate Sensor ◽  
Motion Simulator ◽  
Wide Range ◽  
Mems Gyroscopes ◽  
Mean Square Errors

MEMS (Microelectromechanical System), as an advanced sensor technology, is low power, low cost, and small size. Gyroscope sensor produced with microelectromechanical technology is an angular rate sensor. IMU (Inertial Measurement Unit) sensor for rocket should have a very wide range of measurements. At the beginning of the motion, the rocket accelereation is very high, for which the rocket IMU requires a multisensor with different sensitivity. This paper presents the design of the rocket IMU and its calibration method for all MEMS gyroscopes. Calibration for each sensor is necessary including its varying characteristics. The calibration of the gyroscope sensors use three-axis motion simulator model ST 3176 with resolutions 0.00001 for all axes. Simultaneous calibration was mutually applied which require a short calibration time. The results show that root mean square errors (RMSE) of the calibrated gyroscope for all axes are under 2.5 %. Therefore, that the calibrated gyroscope can be used in the proposed real application.

scholarly journals Robustness against Chirp Signal Interference of On-Board Vehicle Geodetic and Low-Cost GNSS Receivers

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5257
Author(s):  
Franc Dimc ◽  
Polona Pavlovčič-Prešeren ◽  
Matej Bažec
Keyword(s):  
Interference Mitigation ◽  
Low Cost ◽  
Density Ratio ◽  
Autonomous Driving ◽  
Signal Interference ◽  
Noise Power ◽  
Reference Base ◽  
Noise Power Spectral Density ◽  
Processing Abilities ◽  
Gnss Receivers

Robust autonomous driving, as long as it relies on satellite-based positioning, requires carrier-phase-based algorithms, among other types of data sources, to obtain precise and true positions, which is also primarily true for the use of GNSS geodetic receivers, but also increasingly true for mass-market devices. The experiment was conducted under line-of-sight conditions on a straight road during a period of no traffic. The receivers were positioned on the roof of a car travelling at low speed in the presence of a static jammer, while kinematic relative positioning was performed with the static reference base receiver. Interference mitigation techniques in the GNSS receivers used, which were unknown to the authors, were compared using (a) the observed carrier-to-noise power spectral density ratio as an indication of the receivers’ ability to improve signal quality, and (b) the post-processed position solutions based on RINEX-formatted data. The observed carrier-to-noise density generally exerts the expected dependencies and leaves space for comparisons of applied processing abilities in the receivers, while conclusions on the output data results comparison are limited due to the non-synchronized clocks of the receivers. According to our current and previous results, none of the GNSS receivers used in the experiments employs an effective type of complete mitigation technique adapted to the chirp jammer.

scholarly journals Design, manufacture and testing of a prototype obstacle-detection device at blind corners: an automated highway system technology

2020 ◽  
Author(s):  
Charles Atombo ◽  
Emmanuel Gbey ◽  
Apevienyeku Kwami Holali
Keyword(s):  
Traffic Accidents ◽  
Low Cost ◽  
Effective Area ◽  
Obstacle Detection ◽  
The Road ◽  
Vibration Sensors ◽  
Road Signs ◽  
Sensor Module ◽  
Vehicle Path ◽  
Automated Highway

Abstract Traffic accidents on highways are attributed mostly to the "invisibility" of oncoming traffic and road signs. "Speeding" also causes drivers to reduce the effective radius of the vehicle path in the curve, thus trespassing into the lane of the oncoming traffic. The main aim of this paper was to develop a multisensory obstacle-detection device that is affordable, easy to implement and easy to maintain to reduce the risk of road accidents at blind corners. An ultrasonic sensor module with a maximum measuring angle of 15° was used to ensure that a significant portion of the lane was detected at the blind corner. The sensor covered a minimum effective area of 0.5 m2 of the road for obstacle detection. Yellow light was employed to signify caution while negotiating the blind corner. Two photoresistors (PRs) were used as sensors because of the limited number of pins on the microcontroller (Arduino Uno). However, the device developed for this project achieved obstacle detection at blind corners at relatively low cost and can be accessed by all road users. In real-world applications, the use of piezoelectric accelerometers (vibration sensors) instead of PR sensors would be more desirable in order to detect not only cars but also two-wheelers.

scholarly journals Reducing the Influence of Environmental Factors on Performance of a Diffusion-Based Personal Exposure Kit

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4637
Author(s):  
Huixin Zong ◽  
Peter Brimblecombe ◽  
Li Sun ◽  
Peng Wei ◽  
Kin-Fai Ho ◽  
...  
Keyword(s):  
Exposure Assessment ◽  
Real Time ◽  
Low Cost ◽  
Personal Exposure ◽  
Sensor Technology ◽  
Heterogeneous Environments ◽  
Mathematical Algorithms ◽  
Personal Exposure Assessment ◽  
Address System ◽  
The Impact

Sensor technology has enabled the development of portable low-cost monitoring kits that might supplement many applications in conventional monitoring stations. Despite the sensitivity of electrochemical gas sensors to environmental change, they are increasingly important in monitoring polluted microenvironments. The performance of a compact diffusion-based Personal Exposure Kit (PEK) was assessed for real-time gaseous pollutant measurement (CO, O3, and NO2) under typical environmental conditions encountered in the subtropical city of Hong Kong. A dynamic baseline tracking method and a range of calibration protocols to address system performance were explored under practical scenarios to assess the performance of the PEK in reducing the impact of rapid changes in the ambient environment in personal exposure assessment applications. The results show that the accuracy and stability of the ppb level gas measurement is enhanced even in heterogeneous environments, thus avoiding the need for data post-processing with mathematical algorithms, such as multi-linear regression. This establishes the potential for use in personal exposure monitoring, which has been difficult in the past, and for reporting more accurate and reliable data in real-time to support personal exposure assessment and portable air quality monitoring applications.

Dynamic Simulation Control Algorithm Based on the Time Domain

2014 ◽  
Vol 568-570 ◽  
pp. 1020-1025
Author(s):  
Zhuo Wei Jiang ◽  
Chun Ming Gao
Keyword(s):  
Dynamic Simulation ◽  
Time Domain ◽  
Control Algorithm ◽  
Low Cost ◽  
Analog Filter ◽  
Cost Performance ◽  
Dynamic Simulator ◽  
Simulation Control ◽  
The Time Domain ◽  
Computation Speed

In view of badly transplanting of analog filter and low cost performance of digital filter for the washing out signal methods used by dynamic simulator, this paper proposed a computer intelligent time domain method. We decompose signal with the computer intelligence in the time domain, and convert the signal into the corresponding movement form respectively, then get the final result by overlaying them. The experimental results show that this method not only can achieve the effect of the traditional methods, better portability and faster computation speed, but also can be achieved directly on general computers.

scholarly journals High Precision Position Measurement Method for Laguerre-Gaussian Beams Using a Quadrant Detector

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 4007 ◽  
Author(s):  
Qian Li ◽  
Jiabin Wu ◽  
Yunshan Chen ◽  
Jingyuan Wang ◽  
Shijie Gao ◽  
...  
Keyword(s):  
Maximum Error ◽  
Least Square ◽  
New Method ◽  
Beam Radius ◽  
Engineering Practice ◽  
Gaussian Beams ◽  
Good Prospect ◽  
Position Measurement ◽  
Beam Position ◽  
Mean Square Errors

In this paper, we propose a new method to improve the position measurement accuracy for Laguerre-Gaussian beams on a quadrant detector (QD). First, the error effects of the detector diameter and the gap size are taken into account, and the position error compensation factor is introduced into the conventional formula. Then, in order to reduce the number of parameters, the concept of effective radius is proposed. Thus, a new analytical expression is obtained with a best fit using the least square method. It is verified by simulation that this approach can reduce the maximum error by 97.4% when the beam radius is 0.95 mm; meanwhile, the root mean square errors under different radii are all less than 0.004 mm. The results of simulation show that the new method could effectively improve the accuracy of the QD measurement for different radii. Therefore, the new method would have a good prospect in the engineering practice of beam position measurements.

scholarly journals Thermal Modulation of a High-Bandwidth Gas Sensor Array in Real-Time for Application on a Mobile Robot

Proceedings ◽  
2018 ◽  
Vol 2 (13) ◽  
pp. 858 ◽  
Author(s):  
Timothy A. Vincent ◽  
Yuxin Xing ◽  
Marina Cole ◽  
Julian W. Gardner
Keyword(s):  
Signal Processing ◽  
Mobile Robot ◽  
Real Time ◽  
Low Cost ◽  
Processing Technique ◽  
Signal Processing Technique ◽  
Baseline Drift ◽  
Gas Sensor Array ◽  
Sensor Module ◽  
High Bandwidth

A new signal processing technique has been developed for resistive metal oxide (MOX) gas sensors to enable high-bandwidth measurements and enhanced selectivity at PPM levels (<50 PPM VOCs). An embedded micro-heater is thermally pulsed from 225 to 350 °C, which enables the chemical reactions in the sensor film (e.g., SnO2, WO3, NiO) to be extracted using a fast Fourier transform. Signal processing is performed in real-time using a low-cost microcontroller integrated into a sensor module. The approach enables the remove of baseline drift and is resilient to environmental temperature changes. Bench-top experimental results are presented for 50 to 200 ppm of ethanol and CO, which demonstrate our sensor system can be used within a mobile robot.

MODELING AND NUMERICAL SIMULATION OF AN ALGORITHM FOR THE INERTIAL SENSORS ERRORS REDUCTION AND FOR THE INCREASE OF THE STRAP-DOWN NAVIGATOR REDUNDANCY DEGREE IN A LOW COST ARCHITECTURE

2010 ◽  
Vol 34 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Lucian T. Grigorie ◽  
Ruxandra M. Botez
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Lower Cost ◽  
Inertial Sensors ◽  
Low Cost ◽  
Inertial Navigation ◽  
Noise Power ◽  
Integration Algorithm ◽  
The Cost ◽  
Miniaturized Sensors

In this paper, an algorithm for the inertial sensors errors reduction in a strap-down inertial navigation system, using several miniaturized inertial sensors for each axis of the vehicle frame, is conceived. The algorithm is based on the idea of the maximum ratio-combined telecommunications method. We consider that it would be much more advantageous to set a high number of miniaturized sensors on each input axis of the strap-down inertial system instead of a single one, more accurate but expensive and with larger dimensions. Moreover, a redundant system, which would isolate any of the sensors in case of its malfunctioning, is obtained. In order to test the algorithm, Simulink code is used for algorithm and for the acceleration inertial sensors modeling. The Simulink resulted sensors models include their real errors, based on the data sheets parameters, and were conceived based on the IEEE analytical standardized accelerometers model. An integration algorithm is obtained, in which the signal noise power delivered to the navigation processor, is reduced, proportionally with the number of the integrated sensors. At the same time, the bias of the resulted signal is reduced, and provides a high redundancy degree for the strap-down inertial navigation system at a lower cost than at the cost of more accurate and expensive sensors.

Design of Mechaless LiDAR Optical System With Large FOV Using Liquid Lens and Fisheye Lens

2018 ◽  
Author(s):  
Hyun Choi ◽  
Wan-Chin Kim
Keyword(s):  
Low Cost ◽  
Autonomous Driving ◽  
Voltage Regulation ◽  
Field Of View ◽  
Fisheye Lens ◽  
Liquid Lens ◽  
Fine Spatial Resolution ◽  
Flash Lidar ◽  
Optical Phased Array ◽  
Measurable Distance

Mechaless LiDAR technology, which does not have a mechanical drive part, has been actively studied in order to increase the reliability of the LiDAR device at low cost and drive environment in order to more actively apply LiDAR technology to autonomous driving. Mechaless LiDAR technology, which has been mainly studied recently, includes 3D Flash LiDAR technology, MEMS mirror utilization method, and OPA (Optical Phased Array). However, these methods have not been developed rapidly as a key technology for achieving autonomous driving due to low stability of driving environment or remarkably low measurable distance and FOV (field of view) compared with mechanical LiDAR. In this study, we investigated the improvement of FOV by using a flux-deflecting liquid lens and a fisheye lens that can achieve fine spatial resolution through continuous voltage regulation. Based on the initial design results, it was examined that the FOV can be secured to 80 ° or more by utilizing a relatively simple fisheye lens composed of only spherical lenses.

scholarly journals Seasonal Influence on the Performance of Low-Cost NO2 Sensor Calibrations

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7919
Author(s):  
Sjoerd van Ratingen ◽  
Jan Vonk ◽  
Christa Blokhuis ◽  
Joost Wesseling ◽  
Erik Tielemans ◽  
...  
Keyword(s):  
Low Cost ◽  
Added Value ◽  
Sensor Data ◽  
Sensor Technology ◽  
Monitoring Networks ◽  
Technical Problems ◽  
Eu Directive ◽  
Short Period ◽  
No2 Sensor ◽  
One Year

Low-cost sensor technology has been available for several years and has the potential to complement official monitoring networks. The current generation of nitrogen dioxide (NO2) sensors suffers from various technical problems. This study explores the added value of calibration models based on (multiple) linear regression including cross terms on the performance of an electrochemical NO2 sensor, the B43F manufactured by Alphasense. Sensor data were collected in duplicate at four reference sites in the Netherlands over a period of one year. It is shown that a calibration, using O3 and temperature in addition to a reference NO2 measurement, improves the prediction in terms of R2 from less than 0.5 to 0.69–0.84. The uncertainty of the calibrated sensors meets the Data Quality Objective for indicative methods specified by the EU directive in some cases and it was verified that the sensor signal itself remains an important predictor in the multilinear regressions. In practice, these sensors are likely to be calibrated over a period (much) shorter than one year. This study shows the dependence of the quality of the calibrated signal on the choice of these short (monthly) calibration and validation periods. This information will be valuable for determining short-period calibration strategies.

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