scholarly journals Deep Vision Servo Hand-Eye Coordination Planning Study for Sorting Robots

Symmetry ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 152
Author(s):  
Tao Ning ◽  
Changcheng Wang ◽  
Yumeng Han
Keyword(s):  
Large Scale ◽  
Initial Position ◽  
Transformation Model ◽  
Planning Study ◽  
Positioning Accuracy ◽  
Coordination Strategy ◽  
Hand Eye Coordination ◽  
Depth Vision ◽  
Vision Servo ◽  
Sorting Test

Within the context of large-scale symmetry, a study on deep vision servo hand-eye coordination planning for sorting robots was conducted according to the problems of low recognition-sorting accuracy and efficiency in existing sorting robots. In order to maintain the symmetry of the picking robot, a small telescopic sorting robot with RealSense depth vision servo embedded in the manipulator was developed. The workspace and posture of picking parcels were analyzed, and the coordinate transformation model of hand-eye coordination was established for the “Eye-in-hand” mode. The hand-eye coordinated sorting test shows that the average positioning accuracy of the end in the X, Y and Z directions is 3.49 mm, 2.76 mm and 3.32 mm respectively, and the average time is 19.19 s. Among them, the average time for the mechanical arm to pick up the package from the initial position is 12.02 s, the average time for intermediate identification and calculation is 3.79 s, and the average time for placing the package is 6.9 s. The time consumed by robot arm’s action accounts for 79.8% of the whole cycle. The robot structure and the hand-eye coordination strategy with RealSense depth vision servo embedded in the robot can meet picking operation requirements, and the design of a picking robot proposed in this paper can greatly improve the coordination symmetry of fruit target recognition, detection, and picking.

A simple and rapid calibration methodology for industrial robot based on geometric constraint and two-step error

2018 ◽  
Vol 45 (6) ◽  
pp. 715-721 ◽  
Author(s):  
Jiabo Zhang ◽  
Xibin Wang ◽  
Ke Wen ◽  
Yinghao Zhou ◽  
Yi Yue ◽  
...  
Keyword(s):  
Coordinate System ◽  
Large Scale ◽  
Industrial Robot ◽  
Geometric Constraint ◽  
Machining Process ◽  
Kinematic Parameters ◽  
Robot Calibration ◽  
Positioning Accuracy ◽  
Content Type ◽  
Rapid Calibration

Purpose The purpose of this study is the presentation and research of a simple and rapid calibration methodology for industrial robot. Extensive research efforts were devoted to meet the requirements of online compensation, closed-loop feedback control and high-precision machining during the flexible machining process of robot for large-scale cabin. Design/methodology/approach A simple and rapid method to design and construct the transformation relation between the base coordinate system of robot and the measurement coordinate system was proposed based on geometric constraint. By establishing the Denavit–Hartenberg model for robot calibration, a method of two-step error for kinematic parameters calibration was put forward, which aided in achievement of step-by-step calibration of angle and distance errors. Furthermore, KUKA robot was considered as the research object, and related experiments were performed based on laser tracker. Findings The experimental results demonstrated that the accuracy of the coordinate transformation could reach 0.128 mm, which meets the transformation requirements. Compared to other methods used in this study, the calibration method of two-step error could significantly improve the positioning accuracy of robot up to 0.271 mm. Originality/value The methodology based on geometric constraint and two-step error is simple and can rapidly calibrate the kinematic parameters of robot. It also leads to the improvement in the positioning accuracy of robot.

scholarly journals The 23–26 September 2012 U.K. Floods: Using PV Surgery to Quantify Sensitivity to Upper-Level Forcing

2017 ◽  
Vol 145 (10) ◽  
pp. 4055-4079 ◽  
Author(s):  
Sam Hardy ◽  
David M. Schultz ◽  
Geraint Vaughan
Keyword(s):  
United Kingdom ◽  
Large Scale ◽  
Extreme Event ◽  
Initial Conditions ◽  
Initial Position ◽  
River Flooding ◽  
The United Kingdom ◽  
Accumulated Rainfall ◽  
Upper Level ◽  
The Impact

Major river flooding affected the United Kingdom in late September 2012 as a slow-moving extratropical cyclone brought over 150 mm of rain to parts of northern England and north Wales. The cyclone deepened over the United Kingdom on 24–26 September as a potential vorticity (PV) anomaly approached from the northwest, elongated into a PV streamer, and wrapped around the cyclone. The strength and position of the PV anomaly is modified in the initial conditions of Weather Research and Forecasting Model simulations, using PV surgery, to examine whether different upper-level forcing, or different phasing between the PV anomaly and cyclone, could have produced an even more extreme event. These simulations reveal that quasigeostrophic (QG) forcing for ascent ahead of the anomaly contributed to the persistence of the rainfall over the United Kingdom. Moreover, weakening the anomaly resulted in lower rainfall accumulations across the United Kingdom, suggesting that the impact of the event might be proportional to the strength of the upper-level QG forcing. However, when the anomaly was strengthened, it rotated cyclonically around a large-scale trough over Iceland rather than moving eastward as in the verifying analysis, with strongly reduced accumulated rainfall across the United Kingdom. A similar evolution developed when the anomaly was moved farther away from the cyclone. Conversely, moving the anomaly nearer to the cyclone produced a similar solution to the verifying analysis, with slightly increased rainfall totals. These counterintuitive results suggest that the verifying analysis represented almost the highest-impact scenario possible for this flooding event when accounting for sensitivity to the initial position and strength of the PV anomaly.

scholarly journals A Dynamical Initialization Scheme for Real-Time Forecasts of Tropical Cyclones Using the WRF Model*

2013 ◽  
Vol 141 (3) ◽  
pp. 964-986 ◽  
Author(s):  
Dong-Hyun Cha ◽  
Yuqing Wang
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Initial Conditions ◽  
Wrf Model ◽  
Forecast Model ◽  
Initial Position ◽  
Northwest Pacific ◽  
Forecast System ◽  
Positive Effects ◽  
Forecast Models

Abstract To improve the initial conditions of tropical cyclone (TC) forecast models, a dynamical initialization (DI) scheme using cycle runs is developed and implemented into a real-time forecast system for northwest Pacific TCs based on the Weather Research and Forecasting (WRF) Model. In this scheme, cycle runs with a 6-h window before the initial forecast time are repeatedly conducted to spin up the axisymmetric component of the TC vortex until the model TC intensity is comparable to the observed. This is followed by a 72-h forecast using the Global Forecast System (GFS) prediction as lateral boundary conditions. In the DI scheme, the spectral nudging technique is employed during each cycle run to reduce bias in the large-scale environmental field, and the relocation method is applied after the last cycle run to reduce the initial position error. To demonstrate the effectiveness of the proposed DI scheme, 69 forecast experiments with and without the DI are conducted for 13 TCs over the northwest Pacific in 2010 and 2011. The DI shows positive effects on both track and intensity forecasts of TCs, although its overall skill depends strongly on the performance of the GFS forecasts. Compared to the forecasts without the DI, on average, forecasts with the DI reduce the position and intensity errors by 10% and 30%, respectively. The results demonstrate that the proposed DI scheme improves the initial TC vortex structure and intensity and provides warm physics spinup, producing initial states consistent with the forecast model, thus achieving improved track and intensity forecasts.

scholarly journals Socio-Philosophical Bases of Research of Modernization Processes in Uzbekistan

2019 ◽  
Vol 9 (1) ◽  
pp. 3119-3123
Keyword(s):  
Social Sciences ◽  
Large Scale ◽  
Transformation Model ◽  
Development Programs ◽  
Complex State ◽  
Social Sciences And Humanities ◽  
Comprehensive Development ◽  
History Of ◽  
The Republic ◽  
Further Development

Large-scale reforms and complex modernization carried out in the country after independence are studied from the positions of various social sciences and humanities. However, the history of modernization processes in our country has not been paid sufficient attention to the problem of chronological cycles. This chapter examines the philosophical and historical foundations of the complex state of modernization in the republic, and they are divided into specific chronological stages. At the same time, the comprehensive development programs ("Uzbek Model" of Development, the Concept of Intensification of Democratic Reforms and Formation of Civil Society in the Country, Strategy of Action for the Further Development of the Republic of Uzbekistan) for the reform of the Republic of Uzbekistan are taken as a determinant. Accordingly, the peculiarities of the stages of modernization in the Republic of Uzbekistan will be determined and the transformation model of the republic will be opened.

scholarly journals An Improved Bluetooth Indoor Positioning Method Using Dynamic Fingerprint Window

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7269
Author(s):  
Ling Ruan ◽  
Ling Zhang ◽  
Tong Zhou ◽  
Yi Long
Keyword(s):  
Large Scale ◽  
Nearest Neighbor ◽  
Indoor Positioning ◽  
K Nearest Neighbor ◽  
Positioning Accuracy ◽  
Local Clustering ◽  
Positioning Method ◽  
K Nearest Neighbor Algorithm ◽  
Space Range ◽  
Fingerprint Data

The weighted K-nearest neighbor algorithm (WKNN) is easily implemented, and it has been widely applied. In the large-scale positioning regions, using all fingerprint data in matching calculations would lead to high computation expenses, which is not conducive to real-time positioning. Due to signal instability, irrelevant fingerprints reduce the positioning accuracy when performing the matching calculation process. Therefore, selecting the appropriate fingerprint data from the database more quickly and accurately is an urgent problem for improving WKNN. This paper proposes an improved Bluetooth indoor positioning method using a dynamic fingerprint window (DFW-WKNN). The dynamic fingerprint window is a space range for local fingerprint data searching instead of universal searching, and it can be dynamically adjusted according to the indoor pedestrian movement and always covers the maximum possible range of the next positioning. This method was tested and evaluated in two typical scenarios, comparing two existing algorithms, the traditional WKNN and the improved WKNN based on local clustering (LC-WKNN). The experimental results show that the proposed DFW-WKNN algorithm enormously improved both the positioning accuracy and positioning efficiency, significantly, when the fingerprint data increased.

scholarly journals Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection

2017 ◽  
Vol 37 (4-5) ◽  
pp. 421-436 ◽  
Author(s):  
Sergey Levine ◽  
Peter Pastor ◽  
Alex Krizhevsky ◽  
Julian Ibarz ◽  
Deirdre Quillen
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Spatial Relationship ◽  
Robotic Platform ◽  
Robotic Grasping ◽  
Real Time Control ◽  
Time Control ◽  
Wear And Tear ◽  
Hand Eye Coordination ◽  
Novel Objects

We describe a learning-based approach to hand-eye coordination for robotic grasping from monocular images. To learn hand-eye coordination for grasping, we trained a large convolutional neural network to predict the probability that task-space motion of the gripper will result in successful grasps, using only monocular camera images independent of camera calibration or the current robot pose. This requires the network to observe the spatial relationship between the gripper and objects in the scene, thus learning hand-eye coordination. We then use this network to servo the gripper in real time to achieve successful grasps. We describe two large-scale experiments that we conducted on two separate robotic platforms. In the first experiment, about 800,000 grasp attempts were collected over the course of two months, using between 6 and 14 robotic manipulators at any given time, with differences in camera placement and gripper wear and tear. In the second experiment, we used a different robotic platform and 8 robots to collect a dataset consisting of over 900,000 grasp attempts. The second robotic platform was used to test transfer between robots, and the degree to which data from a different set of robots can be used to aid learning. Our experimental results demonstrate that our approach achieves effective real-time control, can successfully grasp novel objects, and corrects mistakes by continuous servoing. Our transfer experiment also illustrates that data from different robots can be combined to learn more reliable and effective grasping.

Uncertainties evaluation of coordinate transformation parameters in the large-scale measurement for aircraft assembly

Sensor Review ◽  
2018 ◽  
Vol 38 (4) ◽  
pp. 542-550 ◽  
Author(s):  
Zhengping Deng ◽  
Shuanggao Li ◽  
Xiang Huang
Keyword(s):  
Measurement Error ◽  
Analytical Method ◽  
Coordinate Transformation ◽  
Large Scale ◽  
Transformation Model ◽  
Individual Measurement ◽  
Content Type ◽  
Aircraft Assembly ◽  
Propagation Law ◽  
Transformation Parameters

Purpose For the measurement of large-scale components in aircraft assembly, the evaluation of coordinate transformation parameters between the coordinate frames of individual measurement systems to the assembly frame is an essential task, which is usually completed by registration of the enhanced reference system (ERS) points. This paper aims to propose an analytical method to evaluate the uncertainties of transformation parameters considering both the measurement error and the deployment error of ERS points. Design/methodology/approach For each measuring station, the measured coordinates of ERS points are first roughly registered to the assembly coordinate system using the singular value decomposition method. Then, a linear transformation model considering the measurement error and deployment error of ERS points is developed, and the analytical solution of transformation parameters’ uncertainties is derived. Moreover, the covariance matrix of each ERS points in the transformation evaluation is calculated based on a new uncertainty ellipsoid model and variance-covariance propagation law. Findings For the transformation of both single and multiple measuring stations, the derived uncertainties of transformation parameters by the proposed analytical method are identical to that obtained by the state-of-the-art iterative method, but the solution process is simpler, and the computation expenses are much less. Originality/value The proposed uncertainty evaluation method would be useful for in-site measurement and optimization of the configuration of ERS points in the design of fixture and large assembly field. It could also be applied to other registration applications with errors on both sides of registration points.

scholarly journals A Time Difference of Arrival-based Localization Algorithm for Wireless Sensor Networks

2016 ◽  
Vol 12 (11) ◽  
pp. 80 ◽  
Author(s):  
Songbo Ji
Keyword(s):  
Wireless Sensor Networks ◽  
Electromagnetic Wave ◽  
Sensor Networks ◽  
Large Scale ◽  
Time Difference ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Time Difference Of Arrival ◽  
Positioning Accuracy ◽  
Simulation Results

<p class="Abstract"><span lang="EN-US">Aimed at solving the problem of local divergence and low data accuracy, this paper introduces a new Time Difference of Arrival(TDOA)-based localization algorithm (TBL) for the large-scale, high-density wireless sensor networks which are designed for real-time surveillance and unexpected incidents management. In particular, several means to improve the accuracy of distance measurement are investigated, and the TDOA method, based on the sound wave and electromagnetic wave to locate in the large-scale WSN, is discussed. Also, the well-designed circular location process has the advantage of better positioning accuracy and coverage percentage. Simulation results have confirmed the effectiveness of the formed TBL algorithm.</span></p>

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