scholarly journals Collaborative Exploration based on Simultaneous Localization and Mapping

Robotics ◽  
2013 ◽  
pp. 1572-1599
Author(s):  
Domenec Puig
Keyword(s):  
Simultaneous Localization And Mapping ◽  
Exploration Time ◽  
Unknown Environments ◽  
Localization And Mapping ◽  
Collaborative Exploration

This chapter focuses on the study of SLAM taking into account different strategies for modeling unknown environments, with the goal of comparing several methodologies and test them in real robots even if they are heterogeneous. The purpose is to combine them in order to reduce the exploration time. Indubitably, it is not an easy work because it is important to take into account the problem of integrating the information related with the changes into the map. In this way, it is necessary to obtain a representation of the surrounding in an efficiently way. Furthermore, the author is interested in the collaboration between robots, because it is well-known that a team of robots is capable of completing a given task faster than a single robot. This assumption will be checked by using both simulations and real robots in different experiments. In addition, the author combines the benefits of both vision-based and laser-based systems in the integration of the algorithms.

Collaborative Exploration Based on Simultaneous Localization and Mapping

2013 ◽  
pp. 303-332
Author(s):  
Domenec Puig
Keyword(s):  
Simultaneous Localization And Mapping ◽  
Exploration Time ◽  
Unknown Environments ◽  
Localization And Mapping ◽  
Collaborative Exploration

This chapter focuses on the study of SLAM taking into account different strategies for modeling unknown environments, with the goal of comparing several methodologies and test them in real robots even if they are heterogeneous. The purpose is to combine them in order to reduce the exploration time. Indubitably, it is not an easy work because it is important to take into account the problem of integrating the information related with the changes into the map. In this way, it is necessary to obtain a representation of the surrounding in an efficiently way. Furthermore, the author is interested in the collaboration between robots, because it is well-known that a team of robots is capable of completing a given task faster than a single robot. This assumption will be checked by using both simulations and real robots in different experiments. In addition, the author combines the benefits of both vision-based and laser-based systems in the integration of the algorithms.

Localization and Mapping for Indoor Navigation

2020 ◽  
pp. 930-954 ◽  
Author(s):  
Heba Gaber ◽  
Mohamed Marey ◽  
Safaa Amin ◽  
Mohamed F. Tolba
Keyword(s):  
System Architecture ◽  
Large Range ◽  
Simultaneous Localization And Mapping ◽  
Indoor Navigation ◽  
Indoor Environments ◽  
Challenging Problem ◽  
Unknown Environments ◽  
Localization And Mapping ◽  
Robotic Missions

Mapping and exploration for the purpose of navigation in unknown or partially unknown environments is a challenging problem, especially in indoor environments where GPS signals can't give the required accuracy. This chapter discusses the main aspects for designing a Simultaneous Localization and Mapping (SLAM) system architecture with the ability to function in situations where map information or current positions are initially unknown or partially unknown and where environment modifications are possible. Achieving this capability makes these systems significantly more autonomous and ideal for a large range of applications, especially indoor navigation for humans and for robotic missions. This chapter surveys the existing algorithms and technologies used for localization and mapping and highlights on using SLAM algorithms for indoor navigation. Also the proposed approach for the current research is presented.

Localization and Mapping for Indoor Navigation

2017 ◽  
pp. 136-160 ◽  
Author(s):  
Heba Gaber ◽  
Mohamed Marey ◽  
Safaa Amin ◽  
Mohamed F. Tolba
Keyword(s):  
System Architecture ◽  
Large Range ◽  
Simultaneous Localization And Mapping ◽  
Indoor Navigation ◽  
Indoor Environments ◽  
Challenging Problem ◽  
Unknown Environments ◽  
Localization And Mapping ◽  
Robotic Missions

Mapping and exploration for the purpose of navigation in unknown or partially unknown environments is a challenging problem, especially in indoor environments where GPS signals can't give the required accuracy. This chapter discusses the main aspects for designing a Simultaneous Localization and Mapping (SLAM) system architecture with the ability to function in situations where map information or current positions are initially unknown or partially unknown and where environment modifications are possible. Achieving this capability makes these systems significantly more autonomous and ideal for a large range of applications, especially indoor navigation for humans and for robotic missions. This chapter surveys the existing algorithms and technologies used for localization and mapping and highlights on using SLAM algorithms for indoor navigation. Also the proposed approach for the current research is presented.

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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