Research

23 pages, 16794 KiB

Open AccessArticle

A Binocular Stereo-Imaging-Perception System with a Wide Field-of-View and Infrared- and Visible Light-Dual-Band Fusion

by Youpan Zhu, Dan Zhang, Yongkang Zhou, Weiqi Jin, Lingling Zhou, Guanlin Wu and Yong Li

Sensors 2024, 24(2), 676; https://doi.org/10.3390/s24020676 - 21 Jan 2024

Viewed by 744

With the continuous evolution of autonomous driving and unmanned driving systems, traditional limitations such as a limited field-of-view, poor ranging accuracy, and real-time display are becoming inadequate to satisfy the requirements of binocular stereo-perception systems. Firstly, we designed a binocular stereo-imaging-perception system with [...] Read more.

With the continuous evolution of autonomous driving and unmanned driving systems, traditional limitations such as a limited field-of-view, poor ranging accuracy, and real-time display are becoming inadequate to satisfy the requirements of binocular stereo-perception systems. Firstly, we designed a binocular stereo-imaging-perception system with a wide-field-of-view and infrared- and visible light-dual-band fusion. Secondly we proposed a binocular stereo-perception optical imaging system with a wide field-of-view of 120.3°, which solves the small field-of-view of current binocular stereo-perception systems. Thirdly, For image aberration caused by the wide-field-of-view system design, we propose an ellipsoidal-image-aberration algorithm with a low consumption of memory resources and no loss of field-of-view. This algorithm simultaneously solves visible light and infrared images with an aberration rate of 45% and 47%, respectively. Fourthly, a multi-scale infrared- and visible light-image-fusion algorithm is used, which improves the situational-awareness capabilities of a binocular stereo-sensing system in a scene and enhances image details to improve ranging accuracy. Furthermore, this paper is based on the Taylor model-calibration binocular stereo-sensing system of internal and external parameters for limit correction; the implemented algorithms are integrated into an NVIDIA Jetson TX2 + FPGA hardware framework, enabling near-distance ranging experiments. The fusion-ranging accuracy within 20 m achieved an error of 0.02 m, outperforming both visible light- and infrared-ranging methods. It generates the fusion-ranging-image output with a minimal delay of only 22.31 ms at a frame rate of 50 Hz. Full article

(This article belongs to the Special Issue Applications of Manufacturing and Measurement Sensors)

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13 pages, 2454 KiB

Open AccessArticle

High-Range and High-Linearity 2D Angle Measurement System for a Fast Steering Mirror

by Boshi Du, Yong Lv, Lishuang Liu and Yang Liu

Sensors 2023, 23(22), 9192; https://doi.org/10.3390/s23229192 - 15 Nov 2023

Viewed by 590

Abstract

In order to solve the problem of the insufficient range of the traditional fast mirror (FSM) angle measurement system in practical applications, a 2D large-angle FSM photoelectric angle measurement system based on the principle of diffuse reflection is proposed. A mathematical model of [...] Read more.

In order to solve the problem of the insufficient range of the traditional fast mirror (FSM) angle measurement system in practical applications, a 2D large-angle FSM photoelectric angle measurement system based on the principle of diffuse reflection is proposed. A mathematical model of the angle measurement system is established by combining the physical properties of the diffuse reflecting plate, such as the rotation angle, rotation center, rotation radius, reflection coefficient and the radius of the diffuse reflecting surface. This paper proposes a method that optimizes the degree of nonlinearity based on this mathematical model. The system is designed and tested. The experimental results show that changing the diffuse reflection surface area can improve the nonlinearity of the angle measurement system effectively. When the radius of the diffuse reflection surface is 3.3 mm, the range is ±20°, the non-linearity is 0.74%, and the resolution can reach up to 2.3″. The system’s body is simple and compact. It is also capable of measuring a wider range of angles while linearity is guaranteed. Full article

(This article belongs to the Special Issue Applications of Manufacturing and Measurement Sensors)

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19 pages, 4389 KiB

Open AccessArticle

A Low-Delay Dynamic Range Compression and Contrast Enhancement Algorithm Based on an Uncooled Infrared Sensor with Local Optimal Contrast

by Youpan Zhu, Yongkang Zhou, Weiqi Jin, Li Zhang, Guanlin Wu and Yiping Shao

Sensors 2023, 23(21), 8860; https://doi.org/10.3390/s23218860 - 31 Oct 2023

Viewed by 732

Abstract

Real-time compression of images with a high dynamic range into those with a low dynamic range while preserving the maximum amount of detail is still a critical technology in infrared image processing. We propose a dynamic range compression and enhancement algorithm for infrared [...] Read more.

Real-time compression of images with a high dynamic range into those with a low dynamic range while preserving the maximum amount of detail is still a critical technology in infrared image processing. We propose a dynamic range compression and enhancement algorithm for infrared images with local optimal contrast (DRCE-LOC). The algorithm has four steps. The first involves blocking the original image to determine the optimal stretching coefficient by using the information of the local block. In the second, the algorithm combines the original image with a low-pass filter to create the background and detailed layers, compressing the background layer with a dynamic range of adaptive gain, and enhancing the detailed layer for the visual characteristics of the human eye. Third, the original image was used as input, the compressed background layer was used as a brightness-guided image, and the local optimal stretching coefficient was used for dynamic range compression. Fourth, an 8-bit image was created (from typical 14-bit input) by merging the enhanced details and the compressed background. Implemented on FPGA, it used 2.2554 Mb of Block RAM, five dividers, and a root calculator with a total image delay of 0.018 s. The study analyzed mainstream algorithms in various scenarios (rich scenes, small targets, and indoor scenes), confirming the proposed algorithm’s superiority in real-time processing, resource utilization, preservation of the image’s details, and visual effects. Full article

(This article belongs to the Special Issue Applications of Manufacturing and Measurement Sensors)

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21 pages, 10991 KiB

Open AccessArticle

Simulation of Laser Profilometer Measurements in the Presence of Speckle Using Perlin Noise

by Sara Roos-Hoefgeest, Mario Roos-Hoefgeest, Ignacio Álvarez and Rafael C. González

Sensors 2023, 23(17), 7624; https://doi.org/10.3390/s23177624 - 02 Sep 2023

Cited by 1 | Viewed by 983

Abstract

In the manufacturing industry, inspection systems play a crucial role in ensuring product quality. High-resolution profilometric sensors have become increasingly popular for inspection due to their ability to provide detailed surface information. However, the development and testing of inspection systems can be costly [...] Read more.

In the manufacturing industry, inspection systems play a crucial role in ensuring product quality. High-resolution profilometric sensors have become increasingly popular for inspection due to their ability to provide detailed surface information. However, the development and testing of inspection systems can be costly and time-consuming. This paper presents the development of a simulation of an inspection system using a high-resolution profilometric sensor. A geometrical and noise model is proposed to simulate the readings of any actual profilometric sensor. The model replicates the sensor’s movement on the CAD model of the inspected part. The model incorporates the physical properties of the sensor and combines noise sources from sensor uncertainty and speckle noise induced by the roughness of the material. Our contribution lies in noise modeling. This work proposes a combination of Perlin noise to simulate the speckle noise and Gaussian noise for the uncertainty-related noise. Perlin noise is generated based on the surface roughness parameters of the inspected part. The accuracy of the simulation system is evaluated by comparing the simulated scans with real scans. The results highlight the ability to simulate real scans of different parts, using commercial sensor specifications and the CAD model of the inspected part. Full article

(This article belongs to the Special Issue Applications of Manufacturing and Measurement Sensors)

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21 pages, 17177 KiB

Open AccessArticle

Sensor Fusion of GNSS and IMU Data for Robust Localization via Smoothed Error State Kalman Filter

by Yuming Yin, Jinhong Zhang, Mengqi Guo, Xiaobin Ning, Yuan Wang and Jianshan Lu

Sensors 2023, 23(7), 3676; https://doi.org/10.3390/s23073676 - 01 Apr 2023

Cited by 5 | Viewed by 4900

Abstract

High−precision and robust localization is critical for intelligent vehicle and transportation systems, while the sensor signal loss or variance could dramatically affect the localization performance. The vehicle localization problem in an environment with Global Navigation Satellite System (GNSS) signal errors is investigated in [...] Read more.

High−precision and robust localization is critical for intelligent vehicle and transportation systems, while the sensor signal loss or variance could dramatically affect the localization performance. The vehicle localization problem in an environment with Global Navigation Satellite System (GNSS) signal errors is investigated in this study. The error state Kalman filtering (ESKF) and Rauch–Tung–Striebel (RTS) smoother are integrated using the data from Inertial Measurement Unit (IMU) and GNSS sensors. A segmented RTS smoothing algorithm is proposed in order to estimate the error state, which is typically close to zero and mostly linear, which allows more accurate linearization and improved state estimation accuracy. The proposed algorithm is evaluated using simulated GNSS signals with and without signal errors. The simulation results demonstrate its superior accuracy and stability for state estimation. The designed ESKF algorithm yielded an approximate 3% improvement in long straight line and turning scenarios compared to classical EKF algorithm. Additionally, the ESKF−RTS algorithm exhibited a 10% increase in the localization accuracy compared to the ESKF algorithm. In the double turning scenarios, the ESKF algorithm resulted in an improvement of about 50% in comparison to the EKF algorithm, while the ESKF−RTS algorithm improved by about 50% compared to the ESKF algorithm. These results indicated that the proposed ESKF−RTS algorithm is more robust and provides more accurate localization. Full article

(This article belongs to the Special Issue Applications of Manufacturing and Measurement Sensors)

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19 pages, 3751 KiB

Open AccessArticle

Sensitivity Analysis of RV Reducer Rotation Error Based on Deep Gaussian Processes

by Shousong Jin, Shulong Shang, Suqi Jiang, Mengyi Cao and Yaliang Wang

Sensors 2023, 23(7), 3579; https://doi.org/10.3390/s23073579 - 29 Mar 2023

Cited by 2 | Viewed by 1449

Abstract

The rotation error is the most important quality characteristic index of a rotate vector (RV) reducer, and it is difficult to accurately optimize the design of a RV reducer, such as the Taguchi type, due to the many factors affecting the rotation error [...] Read more.

The rotation error is the most important quality characteristic index of a rotate vector (RV) reducer, and it is difficult to accurately optimize the design of a RV reducer, such as the Taguchi type, due to the many factors affecting the rotation error and the serious coupling effect among the factors. This paper analyzes the RV reducer rotation error and each factor based on the deep Gaussian processes (DeepGP) model and Sobol sensitivity analysis(SA) method. Firstly, using the optimal Latin hypercube sampling (OLHS) approach and the DeepGP model, a high-precision regression prediction model of the rotation error and each affecting factor was created. On the basis of the prediction model, the Sobol method was used to conduct a global SA of the factors influencing the rotation error and to compare the coupling relationship between the factors. The results show that the OLHS method and the DeepGP model are suitable for predicting the rotation error in this paper, and the accuracy of the prediction model constructed based on both of them is as high as 95%. The rotation error mainly depends on the influencing factors in the second stage cycloidal pinwheel drive part. The primary involute planetary part and planetary output carrier’s rotation error factors have little effect. The coupling effects between the matching clearance between the pin gear and needle gear hole (

δ J

) and the circular position error of the needle gear hole (

δ t

) is noticeably stronger. Full article

(This article belongs to the Special Issue Applications of Manufacturing and Measurement Sensors)

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21 pages, 6969 KiB

Open AccessArticle

A Point Cloud Data-Driven Pallet Pose Estimation Method Using an Active Binocular Vision Sensor

by Yiping Shao, Zhengshuai Fan, Baochang Zhu, Jiansha Lu and Yiding Lang

Sensors 2023, 23(3), 1217; https://doi.org/10.3390/s23031217 - 20 Jan 2023

Cited by 4 | Viewed by 1945

Abstract

Pallet pose estimation is one of the key technologies for automated fork pickup of driverless industrial trucks. Due to the complex working environment and the enormous amount of data, the existing pose estimation approaches cannot meet the working requirements of intelligent logistics equipment [...] Read more.

Pallet pose estimation is one of the key technologies for automated fork pickup of driverless industrial trucks. Due to the complex working environment and the enormous amount of data, the existing pose estimation approaches cannot meet the working requirements of intelligent logistics equipment in terms of high accuracy and real time. A point cloud data-driven pallet pose estimation method using an active binocular vision sensor is proposed, which consists of point cloud preprocessing, Adaptive Gaussian Weight-based Fast Point Feature Histogram extraction and point cloud registration. The proposed method overcomes the shortcomings of traditional pose estimation methods, such as poor robustness, time consumption and low accuracy, and realizes the efficient and accurate estimation of pallet pose for driverless industrial trucks. Compared with traditional Fast Point Feature Histogram and Signature of Histogram of Orientation, the experimental results show that the proposed approach is superior to the above two methods, improving the accuracy by over 35% and reducing the feature extraction time by over 30%, thereby verifying the effectiveness and superiority of the proposed method. Full article

(This article belongs to the Special Issue Applications of Manufacturing and Measurement Sensors)

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18 pages, 4782 KiB

Open AccessArticle

High-Precision Tribometer for Studies of Adhesive Contacts

by Iakov A. Lyashenko, Valentin L. Popov, Roman Pohrt and Vadym Borysiuk

Sensors 2023, 23(1), 456; https://doi.org/10.3390/s23010456 - 01 Jan 2023

Cited by 7 | Viewed by 1732

Abstract

Herein, we describe the design of a laboratory setup operating as a high-precision tribometer. The whole design procedure is presented, starting with a concept, followed by the creation of an exact 3D model and final assembly of all functional parts. The functional idea [...] Read more.

Herein, we describe the design of a laboratory setup operating as a high-precision tribometer. The whole design procedure is presented, starting with a concept, followed by the creation of an exact 3D model and final assembly of all functional parts. The functional idea of the setup is based on a previously designed device that was used to perform more simple tasks. A series of experiments revealed certain disadvantages of the initial setup, for which pertinent solutions were found and implemented. Processing and correction of the data obtained from the device are demonstrated with an example involving backlash and signal drift errors. Correction of both linear and non-linear signal drift errors is considered. We also show that, depending on the research interests, the developed equipment can be further modified by alternating its peripheral parts without changing the main frame of the device. Full article

(This article belongs to the Special Issue Applications of Manufacturing and Measurement Sensors)

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17 pages, 79403 KiB

Open AccessArticle

3D Metrology Using One Camera with Rotating Anamorphic Lenses

by Xiaobo Chen, Jinkai Zhang and Juntong Xi

Sensors 2022, 22(21), 8407; https://doi.org/10.3390/s22218407 - 01 Nov 2022

Viewed by 1654

Abstract

In this paper, a novel 3D metrology method using one camera with rotating anamorphic lenses is presented based on the characteristics of double optical centers for anamorphic imaging. When the anamorphic lens rotates −90° around its optical axis, the 3D data of the [...] Read more.

In this paper, a novel 3D metrology method using one camera with rotating anamorphic lenses is presented based on the characteristics of double optical centers for anamorphic imaging. When the anamorphic lens rotates −90° around its optical axis, the 3D data of the measured object can be reconstructed from the two anamorphic images captured before and after the anamorphic rotation. The anamorphic lens imaging model and a polynomial anamorphic distortion model are firstly proposed. Then, a 3D reconstruction model using one camera with rotating anamorphic lenses is presented. Experiments were carried out to validate the proposed method and evaluate its measurement accuracy. Compared with stereo vision, the main advantage of the proposed 3D metrology approach is the simplicity of point matching, which makes it suitable for developing compact sensors for fast 3D measurements, such as car navigation applications. Full article

(This article belongs to the Special Issue Applications of Manufacturing and Measurement Sensors)

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