Localization in Structured Environments with UWB Devices without Acceleration Measurements, and Velocity Estimation Using a Kalman–Bucy Filter

Alonge, F.; Cusumano, Pasquale; D’Ippolito, Filippo; Garraffa, Giovanni; Livreri, Patrizia; Sferlazza, Antonino

doi:10.3390/s22166308

Cited by 12 publications

(9 citation statements)

References 33 publications

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“…The coordinate data received by the multi-satellite, multi-frequency GNSS antenna used in this study included longitude, latitude, elevation, and other three-dimensional coordinate data, but in agricultural production, the focus of calculation was mainly put on the longitude and latitude. Therefore, it was necessary to convert the received three-dimensional coordinate data into the coordinate data in plane coordinate system according to Mercator projection for further calculation [ 15 ]. The algorithm flow was as follows: Three latitude and longitude coordinates were continuously obtained; three consecutive plane coordinates were obtained by Mercator projection, i.e.,

and

, [ 16 ], as shown in Figure 3 ; and then the turning radius

and center position

of the moving track formed by the tractor position data receiving point were calculated with Formula (1) as below:

where

is the center coordinate, and

is the rotation radius (m) of the moving track formed by the receiver at the top installation position of the tractor.…”

Section: Methodsmentioning

confidence: 99%

Precision Seeding Compensation and Positioning Based on Multisensors

Sun

Zhang

et al. 2022

Sensors

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The current multi-row planter always leads to uneven seeding spacing between rows while seeding in curve paths, which causes uneven growth, a cost increase of production and management, and reduced yield. With the development of smart farming technology, a curve seeding compensation and precise positioning model is proposed in the paper to calculate the real-time speed and position of each seeding unit based on the information from multisensors, such as GNSS and IMU, and to predict the next seeding position to achieve uniform seeding on the curve and improve the unit yield of crops. MATLAB Simulink simulation experiments show that the seeding pass rate of the model is 99.97% when the positioning accuracy is and the traction speed is 1 m/s, and the seeding pass rate of the five-row seeder is as high as 99.81% when the traction speed is 3 m/s, which verifies the effectiveness and practicality of the model.

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and

, [ 16 ], as shown in Figure 3 ; and then the turning radius

and center position

of the moving track formed by the tractor position data receiving point were calculated with Formula (1) as below:

where

is the center coordinate, and

is the rotation radius (m) of the moving track formed by the receiver at the top installation position of the tractor.…”

Section: Methodsmentioning

confidence: 99%

Precision Seeding Compensation and Positioning Based on Multisensors

Sun

Zhang

et al. 2022

Sensors

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“…The satellite signal blockage, high noise levels, multipath effects, and other issues with GPS, on the other hand, make it a less trustworthy alternative sensor for self-localization modules. However, real-time kinematic (RTK) and precise point positioning (PPP) [ 9 ], two GPS technologies that are rapidly developing, can provide locations with decimeter- or centimeter-level precision.…”

Section: Related Workmentioning

confidence: 99%

“…On the one hand, the most common visual odometry sensors are cameras such as RGB cameras [ 5 ], event cameras [ 6 ], and RGB-D cameras [ 7 ]. On the other hand, using the LiDAR sensor [ 8 ] can provide point clouds and a GPS sensor [ 9 , 10 ] can locate the MAV using satellite signals triangulation, as represented in Figure 1 .…”

Section: Introductionmentioning

confidence: 99%

MAV Localization in Large-Scale Environments: A Decoupled Optimization/Filtering Approach

Soliman

Hadj-Abdelkader

Bonardi

et al. 2023

Sensors

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Developing new sensor fusion algorithms has become indispensable to tackle the daunting problem of GPS-aided micro aerial vehicle (MAV) localization in large-scale landscapes. Sensor fusion should guarantee high-accuracy estimation with the least amount of system delay. Towards this goal, we propose a linear optimal state estimation approach for the MAV to avoid complicated and high-latency calculations and an immediate metric-scale recovery paradigm that uses low-rate noisy GPS measurements when available. Our proposed strategy shows how the vision sensor can quickly bootstrap a pose that has been arbitrarily scaled and recovered from various drifts that affect vision-based algorithms. We can consider the camera as a “black-box” pose estimator thanks to our proposed optimization/filtering-based methodology. This maintains the sensor fusion algorithm’s computational complexity and makes it suitable for MAV’s long-term operations in expansive areas. Due to the limited global tracking and localization data from the GPS sensors, our proposal on MAV’s localization solution considers the sensor measurement uncertainty constraints under such circumstances. Extensive quantitative and qualitative analyses utilizing real-world and large-scale MAV sequences demonstrate the higher performance of our technique in comparison to most recent state-of-the-art algorithms in terms of trajectory estimation accuracy and system latency.

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“…It is a communication technology based on ultra wideband, with fast transmission rate, high positioning accuracy, low power consumption, high security, and strong penetration ability. It has been widely applied in various industries [16][17].…”

Section: Principle Of Uwb Positioning Technologymentioning

confidence: 99%

Research and application of box type substation operation safety management and control system based on three-dimensional modeling and UWB positioning

Zhang

Li³

2023

J. Phys.: Conf. Ser.

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This paper proposes a box type substation operation safety management and control system based on GIM modeling technology and UWB positioning technology to address the current challenges of personnel and vehicle control, single control methods, difficult information exchange, and blind spots in on-site substation operations. This system integrates safety control measures throughout the entire operation process of the substation before, during, and after operation, achieving closed-loop control of operation safety. Firstly, laser point cloud and power system GIM technology are used for three-dimensional modeling of substation environment and equipment. Then, UWB positioning technology is used for indoor positioning. Combined with various business systems such as substation work tickets and SCADA, the qualification review of station personnel and vehicles before substation operation is achieved, real-time monitoring of personnel status and movement trajectory during operation, and real-time monitoring of on-site environment after operation are achieved. The system has been deployed and applied to a 35kV box type substation in Guizhou, and through a period of actual operation, it has effectively controlled the operation site.

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Localization in Structured Environments with UWB Devices without Acceleration Measurements, and Velocity Estimation Using a Kalman–Bucy Filter

Cited by 12 publications

References 33 publications

Precision Seeding Compensation and Positioning Based on Multisensors

Precision Seeding Compensation and Positioning Based on Multisensors

MAV Localization in Large-Scale Environments: A Decoupled Optimization/Filtering Approach

Research and application of box type substation operation safety management and control system based on three-dimensional modeling and UWB positioning

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