scholarly journals Crowd-Sourced Mobility Mapping for Location Tracking Using Unlabeled Wi-Fi Simultaneous Localization and Mapping

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Mu Zhou ◽  
Kunjie Xu ◽  
Zengshan Tian ◽  
Haibo Wu ◽  
Ruikang Shi
Keyword(s):  
Simultaneous Localization And Mapping ◽  
Location Based Services ◽  
Alignment Algorithm ◽  
Location Tracking ◽  
Crowd Sourcing ◽  
Coverage Area ◽  
Localization And Mapping ◽  
Vision Sensors ◽  
Clock Location ◽  
Intensive Work

Due to the increasing requirements of the seamless and round-the-clock Location-based services (LBSs), a growing interest in Wi-Fi network aided location tracking is witnessed in the past decade. One of the significant problems of the conventional Wi-Fi location tracking approaches based on received signal strength (RSS) fingerprinting is the time-consuming and labor intensive work involved in location fingerprint calibration. To solve this problem, a novel unlabeled Wi-Fi simultaneous localization and mapping (SLAM) approach is developed to avoid the location fingerprinting and additional inertial or vision sensors. In this approach, an unlabeled mobility map of the coverage area is first constructed by using the crowd-sourcing from a batch of sporadically recorded Wi-Fi RSS sequences based on the spectral cluster assembling. Then, the sequence alignment algorithm is applied to conduct location tracking and mobility map updating. Finally, the effectiveness of this approach is verified by the extensive experiments carried out in a campus-wide area.

scholarly journals A high-efficiency, information-based exploration path planning method for active simultaneous localization and mapping

2020 ◽  
Vol 17 (1) ◽  
pp. 172988142090320
Author(s):  
Peng Li ◽  
Cai-yun Yang ◽  
Rui Wang ◽  
Shuo Wang
Keyword(s):  
Path Planning ◽  
Information Entropy ◽  
High Efficiency ◽  
Dead Reckoning ◽  
Simultaneous Localization And Mapping ◽  
Planning Method ◽  
Coverage Area ◽  
High Coverage ◽  
Full Coverage ◽  
Localization And Mapping

The efficiency of exploration in an unknown scene and full coverage of the scene are essential for a robot to complete simultaneous localization and mapping actively. However, it is challenging for a robot to explore an unknown environment with high efficiency and full coverage autonomously. In this article, we propose a novel exploration path planning method based on information entropy. An information entropy map is first constructed, and its boundary features are extracted. Then a Dijkstra-based algorithm is applied to generate candidate exploration paths based on the boundary features. The dead-reckoning algorithm is used to predict the uncertainty of the robot’s pose along each candidate path. The exploration path is selected based on exploration efficiency and/or high coverage. Simulations and experiments are conducted to evaluate the proposed method’s effectiveness. The results demonstrated that the proposed method achieved not only higher exploration efficiency but also a larger coverage area.

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

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.

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

2020 ◽  
Vol 1682 ◽  
pp. 012049
Author(s):  
Jianjie Zhenga ◽  
Haitao Zhang ◽  
Kai Tang ◽  
Weidi Kong
Keyword(s):  
Simultaneous Localization And Mapping ◽  
Localization And Mapping

scholarly journals Modelling Software Architecture for Visual Simultaneous Localization and Mapping

Automation ◽  
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.

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