Matching for navigation map building for automated guided robot based on laser navigation without a reflector

2019 ◽  
Vol 46 (1) ◽  
pp. 17-30 ◽  
Author(s):  
Ke Zhang ◽  
Hao Gui ◽  
Zhifeng Luo ◽  
Danyang Li
Keyword(s):  
Binary Relation ◽  
Feature Matching ◽  
Rotation Matrix ◽  
Translation Vector ◽  
Local Similarity ◽  
Map Building ◽  
Content Type ◽  
Line Segments ◽  
Feature Line ◽  
Region Search

PurposeLaser navigation without a reflector does not require setup of reflector markers at the scene and thus has the advantages of free path setting and flexible change. This technology has attracted wide attention in recent years and shows great potential in the field of automatic logistics, including map building and locating in real-time according to the environment. This paper aims to focus on the application of feature matching for map building.Design/methodology/approachFirst, an improved linear binary relation algorithm was proposed to calculate the local similarity of the feature line segments, and the matching degree matrix of feature line segments between two adjacent maps was established. Further, rough matching for the two maps was performed, and both the initial rotation matrix and the translation vector for the adjacent map matching were obtained. Then, to improve the rotation matrix, a region search optimization algorithm was proposed, which took the initial rotation matrix as the starting point and searched gradually along a lower error-of-objective function until the error sequence was nonmonotonic. Finally, the random-walk method was proposed to optimize the translation vector by iterating until the error-objective function reached the minimum.FindingsThe experimental results show that the final matching error was controlled within 10 mm after both rotation and translation optimization. Also, the algorithm of map matching and optimization proposed in this paper can realize accurately the feature matching of a laser navigation map and basically meet the real-time navigation and positioning requirements for an automated-guided robot.Originality/valueA linear binary relation algorithm was proposed, and the local similarity between line segments is calculated on the basis of the binary relation. The hill-climbing region search algorithm and the random-walk algorithm were proposed to optimize the rotation matrix and the translation vector, respectively. This algorithm has been applied to industrial production.

scholarly journals A Multi-Feature Fusion Slam System Attaching Semantic Invariant to Points and Lines

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1196
Author(s):  
Gang Li ◽  
Yawen Zeng ◽  
Huilan Huang ◽  
Shaojian Song ◽  
Bin Liu ◽  
...  
Keyword(s):  
Feature Matching ◽  
Feature Fusion ◽  
Error Function ◽  
Line Segments ◽  
Cumulative Error ◽  
Localization And Mapping ◽  
Tracking Process ◽  
Line Features ◽  
Point Line ◽  
Segment Data

The traditional simultaneous localization and mapping (SLAM) system uses static points of the environment as features for real-time localization and mapping. When there are few available point features, the system is difficult to implement. A feasible solution is to introduce line features. In complex scenarios containing rich line segments, the description of line segments is not strongly differentiated, which can lead to incorrect association of line segment data, thus introducing errors into the system and aggravating the cumulative error of the system. To address this problem, a point-line stereo visual SLAM system incorporating semantic invariants is proposed in this paper. This system improves the accuracy of line feature matching by fusing line features with image semantic invariant information. When defining the error function, the semantic invariant is fused with the reprojection error function, and the semantic constraint is applied to reduce the cumulative error of the poses in the long-term tracking process. Experiments on the Office sequence of the TartanAir dataset and the KITTI dataset show that this system improves the matching accuracy of line features and suppresses the cumulative error of the SLAM system to some extent, and the mean relative pose error (RPE) is 1.38 and 0.0593 m, respectively.

A monocular visual measurement system for UAV probe-and-drogue autonomous aerial refueling

2018 ◽  
Vol 11 (2) ◽  
pp. 166-180 ◽  
Author(s):  
Long Xin ◽  
Delin Luo ◽  
Han Li
Keyword(s):  
Measurement System ◽  
Feature Matching ◽  
Perspective Transformation ◽  
High Accuracy ◽  
Noise Elimination ◽  
Aerial Refueling ◽  
Visual Measurement ◽  
Matching Algorithm ◽  
Content Type ◽  
Elimination Algorithm

PurposeThe purpose of this paper is to develop a monocular visual measurement system for autonomous aerial refueling (AAR) for unmanned aerial vehicle, which can process images from an infrared camera to estimate the pose of the drogue in the tanker with high accuracy and real-time performance.Design/methodology/approachMethods and techniques for marker detection, feature matching and pose estimation have been designed and implemented in the visual measurement system.FindingsThe simple blob detection (SBD) method is adopted, which outperforms the Laplacian of Gaussian method. And a novel noise-elimination algorithm is proposed for excluding the noise points. Besides, a novel feature matching algorithm based on perspective transformation is proposed. Comparative experimental results indicated the rapidity and effectiveness of the proposed methods.Practical implicationsThe visual measurement system developed in this paper can be applied to estimate the pose of the drogue with a fast speed and high accuracy and it is a feasible measurement strategy which will considerably increase the autonomy and reliability for AAR.Originality/valueThe SBD method is used to detect the features and a novel noise-elimination algorithm is proposed. Besides, a novel feature matching algorithm based on perspective transformation is proposed which is robust and accurate.

HDPL: a hybrid descriptor for points and lines based on graph neural networks

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zirui Guo ◽  
Huimin Lu ◽  
Qinghua Yu ◽  
Ruibin Guo ◽  
Junhao Xiao ◽  
...  
Keyword(s):  
Neural Network ◽  
Feature Matching ◽  
Feature Descriptor ◽  
Graph Structure ◽  
Multiple Features ◽  
Content Type ◽  
Geometric Relation ◽  
Line Features ◽  
Graph Neural Networks ◽  
Geometric Relationship

Purpose This paper aims to design a novel feature descriptor to improve the performance of feature matching in challenge scenes, such as low texture and wide-baseline scenes. Common descriptors are not suitable for low texture scenes and other challenging scenes mainly owing to encoding only one kind of features. The proposed feature descriptor considers multiple features and their locations, which is more expressive. Design/methodology/approach A graph neural network–based descriptors enhancement algorithm for feature matching is proposed. In this paper, point and line features are the primary concerns. In the graph, commonly used descriptors for points and lines constitute the nodes and the edges are determined by the geometric relationship between points and lines. After the graph convolution designed for incomplete join graph, enhanced descriptors are obtained. Findings Experiments are carried out in indoor, outdoor and low texture scenes. The experiments investigate the real-time performance, rotation invariance, scale invariance, viewpoint invariance and noise sensitivity of the descriptors in three types of scenes. The results show that the enhanced descriptors are robust to scene changes and can be used in wide-baseline matching. Originality/value A graph structure is designed to represent multiple features in an image. In the process of building graph structure, the geometric relation between multiple features is used to establish the edges. Furthermore, a novel hybrid descriptor for points and lines is obtained using graph convolutional neural network. This enhanced descriptor has the advantages of both point features and line features in feature matching.

A novel process planning algorithm for additive and subtractive manufacturing based on skeleton tree matching

2018 ◽  
Vol 24 (2) ◽  
pp. 441-462 ◽  
Author(s):  
Jingbin Hao ◽  
Xin Chen ◽  
Hao Liu ◽  
Shengping Ye
Keyword(s):  
Process Planning ◽  
Feature Matching ◽  
Hybrid Process ◽  
Hybrid Machining ◽  
Hybrid Strategy ◽  
Final Model ◽  
Content Type ◽  
Planning Strategy ◽  
Subtractive Manufacturing ◽  
Planning Algorithm

Purpose To remanufacture a disused part, a hybrid process needs to be taken in part production. Therefore, a reasonable machining route is necessary to be developed for the hybrid process. This paper aims to develop a novel process planning algorithm for additive and subtractive manufacturing (ASM) system to achieve this purpose. Design/methodology/approach First, a skeleton of the model is generated by using thinning algorithm. Then, the skeleton tree is constructed based on topological structure and shape feature. Further, a feature matching algorithm is developed for recognizing the different features between the initial model and the final model based on the skeleton tree. Finally, a reasonable hybrid machining route of the ASM system is generated in consideration of the machining method of each different sub-feature. Findings This paper proposes a hybrid process planning algorithm for the ASM system. Further, it generates new process planning insights on the hybrid process service provider market. Practical implications The proposed process planning algorithm enables engineers to obtain a proper hybrid machining route before product fabrication. And thereby, it extends the machining capability of the hybrid process to manufacture some parts accurately and efficiently. Originality/value This study addresses one gap in the hybrid process literature. It develops the first hybrid process planning strategy for remanufacturing of disused parts based on skeleton tree matching, which generates a more proper hybrid machining route than the currently available hybrid strategy studies. Also, this study provides technical support for the ASM system to repair damaged parts.

scholarly journals Map Merging with Suppositional Box for Multi-Robot Indoor Mapping

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 815
Author(s):  
Baifan Chen ◽  
Siyu Li ◽  
Haowu Zhao ◽  
Limei Liu
Keyword(s):  
Feature Matching ◽  
Transformation Matrix ◽  
Map Building ◽  
Collaborative Mapping ◽  
Matching Pair ◽  
The Right ◽  
Efficiency Map ◽  
Merging Method ◽  
Multi Robot ◽  
Map Merging

For the map building of unknown indoor environment, compared with single robot, multi-robot collaborative mapping has higher efficiency. Map merging is one of the fundamental problems in multi-robot collaborative mapping. However, in the process of grid map merging, image processing methods such as feature matching, as a basic method, are challenged by low feature matching rate. Driven by this challenge, a novel map merging method based on suppositional box that is constructed by right-angled points and vertical lines is proposed. The paper firstly extracts right-angled points of suppositional box selected from the vertical point which is the intersection of the vertical line. Secondly, based on the common edge characteristics between the right-angled points, suppositional box in the map is constructed. Then the transformation matrix is obtained according to the matching pair of suppositional boxes. Finally, for matching errors based on the length of pairs, Kalman filter is used to optimize the transformation matrix. Experimental results show that this method can effectively merge map in different scenes and the successful matching rate is greater than that of other features.

Presenting sustainable supply chain fuzzy rotation matrix framework to manage business challenges in the context of sustainable supply chain management

2019 ◽  
Vol 15 (1) ◽  
pp. 35-49
Author(s):  
Negar Jalilian ◽  
Seyed Habibollah Mirghafoori
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Business Environment ◽  
Rotation Matrix ◽  
Sustainable Supply Chain ◽  
Chain Management ◽  
Content Type ◽  
Sustainable Supply Chain Management ◽  
Hybrid Framework ◽  
Business Challenges

Purpose The purpose of this paper seeks to provide a hybrid framework of sustainable supply chain fuzzy rotation matrix regarding the challenges in today’s business environment and the goals pursued by sustainable supply chain, to prioritize effective infrastructure to manage the challenges in ceramic tile industry in Yazd. Design/methodology/approach The research offers a hybrid framework of analytical hierarchy process (AHP) and quality function deployment (QFD) model to determine, which one of the goals of a sustainable supply chain can have a greater share in the management of business challenges. Findings The results indicated government regulations that encourage the implementation of sustainable supply chain and management of the consumption of non-renewable resources are among the most important infrastructures that can be effective to manage the challenges of today’s business. Practical implications Given the importance of managing the challenges in today’s business environment and sustainable supply chain management capabilities to enable managers to deal with these challenges, the present research makes effort to offer a hybrid framework of AHP and QFD model, to determine, which one of the goals of a sustainable supply chain can have a greater share in the management of business challenges. Originality/value By reviewing the existing research studies in the sustainable supply chain area, it can be found that despite of vast studies, there is no focus on establishing a comprehensive interaction between business challenges management and the fulfillment of sustainable supply chain management goals. So according to this research gap, a new framework was presented in this study to enable tile and ceramic industry managers, to focus on mentioned interaction and manage the businesses challenges in the desired way to achieve sustainable supply chain goals.

Development and evaluation of fast branch-and-bound algorithm for feature matching based on line segments

2007 ◽  
Vol 40 (5) ◽  
pp. 1432-1450 ◽  
Author(s):  
Lik-Kwan Shark ◽  
Andrey A. Kurekin ◽  
Bogdan J. Matuszewski
Keyword(s):  
Branch And Bound ◽  
Feature Matching ◽  
Branch And Bound Algorithm ◽  
Line Segments ◽  
On Line

Detection method of PCB component based on automatic optical stitching algorithm

Circuit World ◽  
2015 ◽  
Vol 41 (4) ◽  
pp. 133-136 ◽  
Author(s):  
Ge Qiang ◽  
Zheng Shanshan ◽  
Zhao Yang ◽  
Chen Mao
Keyword(s):  
Solder Joint ◽  
High Speed ◽  
Feature Matching ◽  
Region Of Interest ◽  
Scale Space ◽  
Image Stitching ◽  
Small Data ◽  
Full Line ◽  
Content Type ◽  
Line Image

Purpose – This paper aims to propose image stitching by reduction of full line and taking line image as registration image to solve the problem of automatic optic inspection in PCB detection. In addition, surf registration was introduced for image stitching to improve the accuracy and speed of stitching. Design/methodology/approach – First, image stitching proceeded by method of full line reduction and taking line image as registration image; second, surf registration was introduced based on the traditional PCB image stitching algorithm. Scale space of the image pyramid was adopted for confirming relative future points between stitching image. The registration means of nearest neighbourhood and next neatest neighborhood was selected for feature matching and fused in region of interest to fulfil image stitching. Findings – The improved stitching algorithm with small data size of image, high speed and noncumulative transitive error eliminated displacement deviation and solved the stitching gap caused by uneven illumination, to greatly improve the accuracy and speed of stitching. Research limitations/implications – The research of this paper can only used for appearance detection and cannot be used for solder joint inspection with circuit detection or invisible solder joint detection; it can identify and mark PCB component defects but cannot classify automatically, thus artificial confirmation and processing is needed. Originality/value – Based on the traditional image stitching means, this paper proposed full line reduction for image stitching, which reduces processing of data and speeds up image stitching; in addition, surf registration was introduced into the study of PCB stitching algorithm, which greatly improves the accuracy and speed of stitching and solves stitching gap formed by opposite variation trend of image local edge caused by uneven illumination.

Sign in / Sign up

Export Citation Format

Share Document