scholarly journals A Tightly-Coupled Positioning System of Online Calibrated RGB-D Camera and Wheel Odometry Based on SE(2) Plane Constraints

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 970
Author(s):  
Liling Zhou ◽  
Yingzi Wang ◽  
Yunfei Liu ◽  
Haifeng Zhang ◽  
Shuaikang Zheng ◽  
...  
Keyword(s):  
Ease Of Use ◽  
Planar Motion ◽  
Technical Solution ◽  
Positioning System ◽  
Two Dimensional ◽  
Transportation Industry ◽  
Positioning Accuracy ◽  
Extrinsic Parameter ◽  
Robot Positioning ◽  
Tightly Coupled

The emergence of Automated Guided Vehicle (AGV) has greatly increased the efficiency of the transportation industry, which put forward the urgent requirement for the accuracy and ease of use of 2D planar motion robot positioning. Multi-sensor fusion positioning has gradually become an important technical route to improve overall efficiency when dealing with AGV positioning. As a sensor directly acquiring depth, the RGB-D camera has received extensive attention in indoor positioning in recent years, while wheel odometry is the sensor that comes with most two-dimensional planar motion robots, and its parameters will not change over time. Both the RGB-D camera and the wheel odometry are commonly used sensors for indoor robot positioning, but the existing research on the fusion of RGB-D and wheel odometry is limited based on classic filtering algorithms; few fusion solutions based on optimization algorithm of them are available at present. To ensure the practicability and greatly improve the accuracy of RGB-D and odometry fusion positioning scheme, this paper proposed a tightly-coupled positioning scheme of online calibrated RGB-D camera and wheel odometry based on SE(2) plane constraints. Experiments have proved that the angle accuracy of the extrinsic parameter in the calibration part is less than 0.5 degrees, and the displacement of the extrinsic parameter reaches the millimeter level. The field-test positioning accuracy of the positioning system we proposed having reached centimeter-level on the dataset without pre-calibration, which is better than ORB-SLAM2 relying solely on RGB-D cameras. The experimental results verify the excellent performance of the frame in positioning accuracy and ease of use and prove that it can be a potential promising technical solution in the field of two-dimensional AGV positioning.

Improvement in a Surface Motor-Driven Planar Motion Stage

2006 ◽  
Vol 18 (6) ◽  
pp. 808-815 ◽  
Author(s):  
Wei Gao ◽  
◽  
Katsutoshi Horie ◽  
Songyi Dian ◽  
Kei Katakura ◽  
...  
Keyword(s):  
Measurement Errors ◽  
Planar Motion ◽  
Two Dimensional ◽  
Positioning Accuracy ◽  
Accuracy Measurement ◽  
Linear Motors ◽  
Stator Windings ◽  
Motion Stage ◽  
Planar Motion Stage ◽  
Sinusoidal Surface

We report a surface motor-driven planar motion stage with an XYθZsurface encoder. The surface motor consists of two pairs of linear motors. Magnetic arrays are installed on the platen and stator windings of linear motors on the stage base. The platen is moved in the X and Y directions by X and Y linear motors. It is rotated around the Z axis by moment generated by the X or Y linear motors. The surface encoder consists of two two-dimensional (2D) angle sensors and an angle grid with 2D sinusoidal surface waves. The angle grid is installed on the platen. Sensors onside make the stage compact. The surface encoder is improved for higher positioning accuracy. Measurement errors of the surface encoder using two detectors – a quadrant PD and 2D PSD – are determined by simulation. The surface motor for increasing stage speed is modified. We conducted experiments comparing the previous prototype stage (Prototype I) and the improved stage (Prototype II).

scholarly journals Temperature-Compensated Spread Spectrum Sound-Based Local Positioning System for Greenhouse Operations

IoT ◽  
2020 ◽  
Vol 1 (2) ◽  
pp. 147-160
Author(s):  
Lok Wai Jacky Tsay ◽  
Tomoo Shiigi ◽  
Zichen Huang ◽  
Xunyue Zhao ◽  
Tetsuhito Suzuki ◽  
...  
Keyword(s):  
Sound Velocity ◽  
Spread Spectrum ◽  
Current System ◽  
Low Cost ◽  
Temporal Variations ◽  
Major Effect ◽  
Ease Of Use ◽  
Positioning System ◽  
Positioning Accuracy ◽  
Local Positioning System

A spread spectrum sound-based local positioning system (SSSLPS) has been developed for indoor agricultural robots by our research group. Such an SSSLPS has several advantages, including effective propagation, low cost, and ease of use. When using sound velocity for field position measurements in a greenhouse, spatial and temporal variations in temperature during the day can have a major effect on sound velocity and subsequent positioning accuracy. In this research, a temperature-compensated sound velocity positioning was proposed and evaluated in comparison to a conventional temperature sensor method. Results indicate that this new proposed method has a positioning accuracy to within 20 mm in a 3 m × 9 m ridged greenhouse. It has the potential to replace the current system of using the temperature sensors in a greenhouse.

Study on Precision Positioning System of Two-Dimensional Platform Based on High-Speed and Large-Range

2008 ◽  
Author(s):  
Chuan Yang ◽  
Zhi Zhang
Keyword(s):  
Pid Control ◽  
High Speed ◽  
Large Range ◽  
Experimental Results ◽  
Positioning System ◽  
Two Dimensional ◽  
Precision Positioning ◽  
Positioning Accuracy ◽  
Ultra Precision ◽  
Self Adaptive

A two-dimensional ultra-precision positioning system with high-speed and large-range which can be used for micro-nanometer machining has been studied out in this paper. Macro and micro moving system are used to meet the demands of ultra-precision positioning with high-speed and large-range. According to the demands of macro moving system, a valid control of fuzzy-neuron self-adaptive and weighted PID control algorithm with high speed and high precision is proposed. The experimental results show that the error of repeated positioning accuracy is less than 1 μ m for a random point within the range of 300mm by 300mm under the design load for a carrying test-bed with carrying area of 250mm by 250mm. According to the demands of micro moving system, self-adaptive and fuzzy reasoning PID control system based on neural network is studied for the first time. The experimental results show that repeated positioning accuracy is less than 100nm.

Dynamic and Positioning Performances of Linear Electromechanical Actuator

2015 ◽  
Vol 809-810 ◽  
pp. 682-687
Author(s):  
Vasile Nasui ◽  
Mihai Banica ◽  
Dinu Darabă
Keyword(s):  
Dynamic Characteristics ◽  
Practical Importance ◽  
Correct Identification ◽  
Positioning System ◽  
Positioning Error ◽  
Servo Motor ◽  
Positioning Accuracy ◽  
Electromechanical Actuator ◽  
Initial Errors ◽  
Selection For

This paper presents the dynamic characteristics and the proposed positioning performance of the system to them investigated experimentally. In this research, we developed the positioning system and we evaluated positioning accuracy. The developed system uses a servo motor for motion actuation. In this paper, we focused on studying the dependency of the positioning error – elementary errors – the position of the conducting element for the mechanism of the transformation of the rotation translation movement, representatively the mechanism screw – screwdriver and on emphasizing the practical consequences in the field of design, regulation and exploitation of the correct identification of all the initial errors in the structure of the mechanism, their character and the selection for an ultimate calculus of these which are of a real practical importance.

scholarly journals Improvement of Heavy Load Robot Positioning Accuracy by Combining a Model-Based Identification for Geometric Parameters and an Optimized Neural Network for the Compensation of Nongeometric Errors

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yuxiang Wang ◽  
Zhangwei Chen ◽  
Hongfei Zu ◽  
Xiang Zhang ◽  
Chentao Mao ◽  
...  
Keyword(s):  
Neural Network ◽  
Manufacturing Systems ◽  
Robot Manipulator ◽  
Joint Stiffness ◽  
Calibration Method ◽  
Geometric Parameters ◽  
Heavy Load ◽  
Positioning Accuracy ◽  
Robot Positioning ◽  
Residual Errors

The positioning accuracy of a robot is of great significance in advanced robotic manufacturing systems. This paper proposes a novel calibration method for improving robot positioning accuracy. First of all, geometric parameters are identified on the basis of the product of exponentials (POE) formula. The errors of the reduction ratio and the coupling ratio are identified at the same time. Then, joint stiffness identification is carried out by adding a load to the end-effector. Finally, residual errors caused by nongeometric parameters are compensated by a multilayer perceptron neural network (MLPNN) based on beetle swarm optimization algorithm. The calibration is implemented on a SIASUN SR210D robot manipulator. Results show that the proposed method possesses better performance in terms of faster convergence and higher precision.

scholarly journals Cobot User Frame Calibration: Evaluation and Comparison between Positioning Repeatability Performances Achieved by Traditional and Vision-Based Methods

Robotics ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 45
Author(s):  
Roberto Pagani ◽  
Cristina Nuzzi ◽  
Marco Ghidelli ◽  
Alberto Borboni ◽  
Matteo Lancini ◽  
...  
Keyword(s):  
Quantitative Analysis ◽  
Production Line ◽  
Calibration Method ◽  
Fiducial Marker ◽  
Positioning System ◽  
Local Calibration ◽  
Calibration Methods ◽  
Robot Positioning ◽  
Good Repeatability ◽  
Calibration Time

Since cobots are designed to be flexible, they are frequently repositioned to change the production line according to the needs; hence, their working area (user frame) needs to be often calibrated. Therefore, it is important to adopt a fast and intuitive user frame calibration method that allows even non-expert users to perform the procedure effectively, reducing the possible mistakes that may arise in such contexts. The aim of this work was to quantitatively assess the performance of different user frame calibration procedures in terms of accuracy, complexity, and calibration time, to allow a reliable choice of which calibration method to adopt and the number of calibration points to use, given the requirements of the specific application. This has been done by first analyzing the performances of a Rethink Robotics Sawyer robot built-in user frame calibration method (Robot Positioning System, RPS) based on the analysis of a fiducial marker distortion obtained from the image acquired by the wrist camera. This resulted in a quantitative analysis of the limitations of this approach that only computes local calibration planes, highlighting the reduction of performances observed. Hence, the analysis focused on the comparison between two traditional calibration methods involving rigid markers to determine the best number of calibration points to adopt to achieve good repeatability performances. The analysis shows that, among the three methods, the RPS one resulted in very poor repeatability performances (1.42 mm), while the three and five points calibration methods achieve lower values (0.33 mm and 0.12 mm, respectively) which are closer to the reference repeatability (0.08 mm). Moreover, comparing the overall calibration times achieved by the three methods, it is shown that, incrementing the number of calibration points to more than five, it is not suggested since it could lead to a plateau in the performances, while increasing the overall calibration time.

scholarly journals Improved Visible Light-Based Indoor Positioning System Using Machine Learning Classification and Regression

2019 ◽  
Vol 9 (6) ◽  
pp. 1048 ◽  
Author(s):  
Huy Tran ◽  
Cheolkeun Ha
Keyword(s):  
Machine Learning ◽  
Visible Light ◽  
Noise Reduction ◽  
Indoor Positioning ◽  
Computational Time ◽  
Dual Function ◽  
Positioning System ◽  
Positioning Accuracy ◽  
Positioning Systems ◽  
Machine Learning Classification

Recently, indoor positioning systems have attracted a great deal of research attention, as they have a variety of applications in the fields of science and industry. In this study, we propose an innovative and easily implemented solution for indoor positioning. The solution is based on an indoor visible light positioning system and dual-function machine learning (ML) algorithms. Our solution increases positioning accuracy under the negative effect of multipath reflections and decreases the computational time for ML algorithms. Initially, we perform a noise reduction process to eliminate low-intensity reflective signals and minimize noise. Then, we divide the floor of the room into two separate areas using the ML classification function. This significantly reduces the computational time and partially improves the positioning accuracy of our system. Finally, the regression function of those ML algorithms is applied to predict the location of the optical receiver. By using extensive computer simulations, we have demonstrated that the execution time required by certain dual-function algorithms to determine indoor positioning is decreased after area division and noise reduction have been applied. In the best case, the proposed solution took 78.26% less time and provided a 52.55% improvement in positioning accuracy.

Application of Fuzzy PI control to improve the positioning accuracy of a rotary-linear motor driven by two-dimensional ultrasonic actuators

2000 ◽  
Vol 24 (2) ◽  
pp. 105-112 ◽  
Author(s):  
M Kinouchi ◽  
I Hayashi ◽  
N Iwatsuki ◽  
K Morikawa ◽  
J Shibata ◽  
...  
Keyword(s):  
Linear Motor ◽  
Pi Control ◽  
Two Dimensional ◽  
Positioning Accuracy

scholarly journals An Ultra-Short Baseline Underwater Positioning System with Kalman Filtering

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 143
Author(s):  
Qinghua Luo ◽  
Xiaozhen Yan ◽  
Chunyu Ju ◽  
Yunsai Chen ◽  
Zhenhua Luo
Keyword(s):  
Phase Difference ◽  
Kalman Filtering ◽  
Negative Impact ◽  
Minimum Mean Square Error ◽  
Acoustic Signals ◽  
Positioning System ◽  
Short Baseline ◽  
Positioning Accuracy ◽  
Wrong Decision ◽  
Underwater Positioning

The ultra-short baseline underwater positioning is one of the most widely applied methods in underwater positioning and navigation due to its simplicity, efficiency, low cost, and accuracy. However, there exists environmental noise, which has negative impacts on the positioning accuracy during the ultra-short baseline (USBL) positioning process, which results in a large positioning error. The positioning result may lead to wrong decision-making in the latter processing. So, it is necessary to consider the error sources, and take effective measurements to minimize the negative impact of the noise. In our work, we propose a USBL positioning system with Kalman filtering to improve the positioning accuracy. In this system, we first explore a new kind of element array to accurately capture the acoustic signals from the object. We then organically combine the Kalman filters with the array elements to filter the acoustic signals, using the minimum mean-square error rule to obtain accurate acoustic signals. We got the high-precision phase difference information based on the non-equidistant quaternary original array and the phase difference acquisition mechanism. Finally, on account of the obtained accurate phase difference information and position calculation, we determined the coordinates of the underwater target. Comprehensive evaluation results demonstrate that our proposed USBL positioning method based on the Kalman filter algorithm can effectively enhance the positioning accuracy.

Design of a Flexure-Based Active Fixture System for Precision Robotic Deburring

2018 ◽  
Author(s):  
Jacob Beck ◽  
Burak Sencer ◽  
Ravi Balasubramanian ◽  
Jordan Meader
Keyword(s):  
High Resolution ◽  
Force Control ◽  
Cutting Forces ◽  
Robotic Manipulators ◽  
Positioning System ◽  
Motion Generation ◽  
Positioning Accuracy ◽  
High Compliance ◽  
Dual Stage ◽  
Fixture System

This paper presents on the design, prototyping and testing of a flexure-based active workpiece fixture system for precision robotic deburring. Current industrial robotic manipulators suffer from poor positioning accuracy, which makes precision tasks such as deburring, polishing and grinding challenging. Together, the robotic manipulator and the proposed active work fixture will create a dual-stage positioning system for precision tasks where position/force control is crucial. The main application is robotic deburring, which demands positioning accuracy and high compliance over large cutting forces. This first prototype active fixture system is designed as a planar motion table that is supported by parallel flexures, driven by voice-coil actuators, and uses high-resolution laser displacement pickups facilitate accurate motion generation with great backdrivability for force control. The theory behind the proposed design is shown, and a prototype is then used to validate performance. Overall the prototype flexure stage achieves a total stroke of 1 mm and a bandwidth of 21 Hz.

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