Potential-Field-Based Active Exploration for Acoustic Simultaneous Localization and Mapping

2018 ◽  
Author(s):  
Christopher Schymura ◽  
Dorothea Kolossa
Keyword(s):  
Potential Field ◽  
Simultaneous Localization And Mapping ◽  
Localization And Mapping ◽  
Active Exploration

Research on Obstacles Avoidance for UAV SLAM

2014 ◽  
Vol 635-637 ◽  
pp. 1329-1334 ◽  
Author(s):  
Li Wang ◽  
Xu Liu ◽  
Heng Xin Wang ◽  
Xi Bin Wang
Keyword(s):  
Obstacle Avoidance ◽  
Potential Field ◽  
Simultaneous Localization And Mapping ◽  
Plane Motion ◽  
Artificial Potential Field ◽  
Motion Model ◽  
Field Function ◽  
Moving Obstacles ◽  
Localization And Mapping

Abstract: When UAV is implementing the simultaneous localization and mapping (SLAM) problem, the environment where UAV is flying exists unavoidable solid or moving obstacles because of its unknown character, which threatens the flying safety and the completeness of SLAM mission. To conquer this problem, an improved artificial potential field algorithm is proposed to simultaneously accomplish obstacle avoidance of UAV and SLAM mission based on a potential field function containing the distance from UAV to the goal and from UAV to the obstacles and the covariance of features. This algorithm is simulated and tested based on the built UAV plane motion model. The result shows that the proposed algorithm is effective to avoid the obstacles while implementing SLAM for UAV.

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.

Bag-of-words-driven, single-camera simultaneous localization and mapping

2010 ◽  
Vol 28 (2) ◽  
pp. 204-226 ◽  
Author(s):  
Tom Botterill ◽  
Steven Mills ◽  
Richard Green
Keyword(s):  
Simultaneous Localization And Mapping ◽  
Single Camera ◽  
Bag Of Words ◽  
Localization And Mapping
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