2A2-H07 Simultaneous Localization and Road Boundary Classification Using Digital Street Maps and a 3D Scanner(Localization and Mapping(2))

In the industrial environment, Autonomous Guided Vehicles (AGVs) generally run on a planned route. Among trajectory-tracking algorithms for unmanned vehicles, the Pure Pursuit (PP) algorithm is prevalent in many real-world applications because of its simple and easy implementation. However, it is challenging to decelerate the AGV’s moving speed when turning on a large curve path. Moreover, this paper addresses the kidnapped-robot problem occurring in spare LiDAR environments. This paper proposes an improved Pure Pursuit algorithm so that the AGV can predict the trajectory and decelerate for turning, thus increasing the accuracy of the path tracking. To solve the kidnapped-robot problem, we use a learning-based classifier to detect the repetitive pattern scenario (e.g., long corridor) regarding 2D LiDAR features for switching the localization system between Simultaneous Localization And Mapping (SLAM) method and Odometer method. As experimental results in practice, the improved Pure Pursuit algorithm can reduce the tracking error while performing more efficiently. Moreover, the learning-based localization selection strategy helps the robot navigation task achieve stable performance, with 36.25% in completion rate more than only using SLAM. The results demonstrate that the proposed method is feasible and reliable in actual conditions.

Download Full-text

Comparison of different SLAM approaches for a driverless race car

tm - Technisches Messen ◽

10.1515/teme-2021-0004 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Nick Le Large ◽

Frank Bieder ◽

Martin Lauer

Keyword(s):

Kalman Filter ◽

Extended Kalman Filter ◽

Ground Truth ◽

Time Constraints ◽

Differential Gps ◽

Real World Data ◽

Race Car ◽

Localization And Mapping ◽

Slam Algorithm ◽

Computational Resources

Abstract For the application of an automated, driverless race car, we aim to assure high map and localization quality for successful driving on previously unknown, narrow race tracks. To achieve this goal, it is essential to choose an algorithm that fulfills the requirements in terms of accuracy, computational resources and run time. We propose both a filter-based and a smoothing-based Simultaneous Localization and Mapping (SLAM) algorithm and evaluate them using real-world data collected by a Formula Student Driverless race car. The accuracy is measured by comparing the SLAM-generated map to a ground truth map which was acquired using high-precision Differential GPS (DGPS) measurements. The results of the evaluation show that both algorithms meet required time constraints thanks to a parallelized architecture, with GraphSLAM draining the computational resources much faster than Extended Kalman Filter (EKF) SLAM. However, the analysis of the maps generated by the algorithms shows that GraphSLAM outperforms EKF SLAM in terms of accuracy.

Download Full-text

A survey: which features are required for dynamic visual simultaneous localization and mapping?

Visual Computing for Industry Biomedicine and Art ◽

10.1186/s42492-021-00086-w ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Zewen Xu ◽

Zheng Rong ◽

Yihong Wu

Keyword(s):

Simultaneous Localization And Mapping ◽

Dynamic Environments ◽

Visual Features ◽

Advantages And Disadvantages ◽

Intelligent Robots ◽

Localization And Mapping ◽

High Level ◽

Static World ◽

Robotic Applications ◽

Significant Attention

AbstractIn recent years, simultaneous localization and mapping in dynamic environments (dynamic SLAM) has attracted significant attention from both academia and industry. Some pioneering work on this technique has expanded the potential of robotic applications. Compared to standard SLAM under the static world assumption, dynamic SLAM divides features into static and dynamic categories and leverages each type of feature properly. Therefore, dynamic SLAM can provide more robust localization for intelligent robots that operate in complex dynamic environments. Additionally, to meet the demands of some high-level tasks, dynamic SLAM can be integrated with multiple object tracking. This article presents a survey on dynamic SLAM from the perspective of feature choices. A discussion of the advantages and disadvantages of different visual features is provided in this article.

Download Full-text

A 3D Scanner System for Building the Prosthetic Leg Model Based on the Reality Capture Technique

Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture ◽

10.1145/3421766.3421787 ◽

2020 ◽

Author(s):

Yiming Zhao

Keyword(s):

3D Scanner ◽

Model Based ◽

Capture Technique

Download Full-text

Research on Laser-Visual Fusion-based Simultaneous Localization and Mapping

Journal of Physics Conference Series ◽

10.1088/1742-6596/1682/1/012049 ◽

2020 ◽

Vol 1682 ◽

pp. 012049

Author(s):

Jianjie Zhenga ◽

Haitao Zhang ◽

Kai Tang ◽

Weidi Kong

Keyword(s):

Simultaneous Localization And Mapping ◽

Localization And Mapping

Download Full-text

Structured-light 3D scanning of exhibited historical clothing—a first-ever methodical trial and its results

Heritage Science ◽

10.1186/s40494-021-00544-x ◽

2021 ◽

Vol 9 (1) ◽

Author(s):

Jerzy Montusiewicz ◽

Marek Miłosz ◽

Jacek Kęsik ◽

Kamil Żyła

Keyword(s):

Cultural Heritage ◽

Information Technologies ◽

Structured Light ◽

Three Dimensional ◽

3D Models ◽

3D Scanning ◽

Dimensional Representation ◽

3D Scanner ◽

Three Dimensional Representation ◽

3D Scanners

AbstractHistorical costumes are part of cultural heritage. Unlike architectural monuments, they are very fragile, which exacerbates the problems of their protection and popularisation. A big help in this can be the digitisation of their appearance, preferably using modern techniques of three-dimensional representation (3D). The article presents the results of the search for examples and methodologies of implementing 3D scanning of exhibited historical clothes as well as the attendant problems. From a review of scientific literature it turns out that so far practically no one in the world has made any methodical attempts at scanning historical clothes using structured-light 3D scanners (SLS) and developing an appropriate methodology. The vast majority of methods for creating 3D models of clothes used photogrammetry and 3D modelling software. Therefore, an innovative approach was proposed to the problem of creating 3D models of exhibited historical clothes through their digitalisation by means of a 3D scanner using structural light technology. A proposal for the methodology of this process and concrete examples of its implementation and results are presented. The problems related to the scanning of 3D historical clothes are also described, as well as a proposal how to solve them or minimise their impact. The implementation of the methodology is presented on the example of scanning elements of the Emir of Bukhara's costume (Uzbekistan) from the end of the nineteenth century, consisting of the gown, turban and shoes. Moreover, the way of using 3D models and information technologies to popularise cultural heritage in the space of digital resources is also discussed.

Download Full-text

A V-SLAM Guided and Portable System for Photogrammetric Applications

Remote Sensing ◽

10.3390/rs13122351 ◽

2021 ◽

Vol 13 (12) ◽

pp. 2351

Author(s):

Alessandro Torresani ◽

Fabio Menna ◽

Roberto Battisti ◽

Fabio Remondino

Keyword(s):

Low Cost ◽

Cost Effective ◽

Motion Blur ◽

Guidance System ◽

Prototype System ◽

Active Sensors ◽

Localization And Mapping ◽

Acquisition Speed ◽

Mobile Mapping System ◽

Slam Algorithm

Mobile and handheld mapping systems are becoming widely used nowadays as fast and cost-effective data acquisition systems for 3D reconstruction purposes. While most of the research and commercial systems are based on active sensors, solutions employing only cameras and photogrammetry are attracting more and more interest due to their significantly minor costs, size and power consumption. In this work we propose an ARM-based, low-cost and lightweight stereo vision mobile mapping system based on a Visual Simultaneous Localization And Mapping (V-SLAM) algorithm. The prototype system, named GuPho (Guided Photogrammetric System) also integrates an in-house guidance system which enables optimized image acquisitions, robust management of the cameras and feedback on positioning and acquisition speed. The presented results show the effectiveness of the developed prototype in mapping large scenarios, enabling motion blur prevention, robust camera exposure control and achieving accurate 3D results.

Download Full-text

Modelling Software Architecture for Visual Simultaneous Localization and Mapping

Automation ◽

10.3390/automation2020003 ◽

2021 ◽

Vol 2 (2) ◽

pp. 48-61

Author(s):

Bhavyansh Mishra ◽

Robert Griffin ◽

Hakki Erhan Sevil

Keyword(s):

System Integration ◽

Ad Hoc ◽

Simultaneous Localization And Mapping ◽

Software Systems ◽

Model Driven ◽

Performance Improvements ◽

Software Model ◽

Localization And Mapping ◽

Stereo Cameras ◽

Core Components

Visual simultaneous localization and mapping (VSLAM) is an essential technique used in areas such as robotics and augmented reality for pose estimation and 3D mapping. Research on VSLAM using both monocular and stereo cameras has grown significantly over the last two decades. There is, therefore, a need for emphasis on a comprehensive review of the evolving architecture of such algorithms in the literature. Although VSLAM algorithm pipelines share similar mathematical backbones, their implementations are individualized and the ad hoc nature of the interfacing between different modules of VSLAM pipelines complicates code reuseability and maintenance. This paper presents a software model for core components of VSLAM implementations and interfaces that govern data flow between them while also attempting to preserve the elements that offer performance improvements over the evolution of VSLAM architectures. The framework presented in this paper employs principles from model-driven engineering (MDE), which are used extensively in the development of large and complicated software systems. The presented VSLAM framework will assist researchers in improving the performance of individual modules of VSLAM while not having to spend time on system integration of those modules into VSLAM pipelines.

Download Full-text