Results 241 to 250 of about 2,238,929 (282)

A Real-Time, Robust, and Versatile Visual-SLAM Framework Based on Deep Learning Networks

IEEE Transactions on Instrumentation and Measurement
In this article, we investigate the paradigm of deep learning techniques to enhance the performance of visual-based simultaneous localization and mapping (vSLAM) systems, particularly in challenging environments. By leveraging deep feature extraction and
Xiao Zhang, Hongbin Dong, Haoxin Zhang, Xiaozhou Zhu, Shuaixin Li, Baosong Deng   +5 more
semanticscholar   +1 more source

Deterministic topological visual SLAM

Proceedings of the Fifth Symposium on Information and Communication Technology - SoICT '14, 2014
Simultaneous Localization and Mapping (SLAM) addresses the task of building a map of the environment with a robot while simultaneously localizing the robot relative to that map. SLAM is generally regarded as one of the most important problem in the pursuit of building truly autonomous mobile robots and is typically expressed within a probabilistic ...
Hui Wang, Michael Jenkin, Patrick Dymond
openaire   +1 more source

DOG-SLAM: Enhancing Dynamic Visual SLAM Precision Through GMM-Based Dynamic Object Removal and ORB-Boost

IEEE Transactions on Instrumentation and Measurement
Accurate mapping and navigation in dynamic environments pose substantial challenges for autonomous robotics. Traditional visual simultaneous localization and mapping (Visual SLAM) methods frequently encounter difficulties with dynamic elements, leading ...
Jiming Long, Fei Wang, Mingyang Liu, Yu Wang, Qiang Zou   +4 more
semanticscholar   +1 more source

AirSLAM: An Efficient and Illumination-Robust Point-Line Visual SLAM System

IEEE Transactions on robotics
In this article, we present an efficient visual simultaneous localization and mapping (SLAM) system designed to tackle both short-term and long-term illumination challenges.
Kuan Xu, Y. Hao, Shenghai Yuan, Chen Wang, Lihua Xie   +4 more
semanticscholar   +1 more source

DN-SLAM: A Visual SLAM With ORB Features and NeRF Mapping in Dynamic Environments

IEEE Sensors Journal
Vision simultaneous localization and mapping (SLAM) is essential for adapting to new environments and for localization and is therefore widely used in robotics.
Chenyu Ruan, Qiuyu Zang, Kehua Zhang, Kai Huang   +3 more
semanticscholar   +1 more source

A Survey of Visual SLAM in Dynamic Environment: The Evolution From Geometric to Semantic Approaches

IEEE Transactions on Instrumentation and Measurement
Simultaneous localization and mapping (SLAM) is crucial for the progression of autonomous systems, including autonomous driving, augmented reality (AR), and robotics.
Yanan Wang, Yaobin Tian, Jiawei Chen, Kun Xu, Xilun Ding   +4 more
semanticscholar   +1 more source

RSO-SLAM: A Robust Semantic Visual SLAM With Optical Flow in Complex Dynamic Environments

IEEE transactions on intelligent transportation systems (Print)
Visual Simultaneous Localization and Mapping (VSLAM) has undergone gradual development and found widespread application. However, existing VSLAM systems predominantly rely on static environment assumptions, leading to diminished robustness and ...
Liang Qin, Chang Wu, Zhenyu Chen, Xiao-jiang Kong, Zejie Lv, Zhiqi Zhao   +5 more
semanticscholar   +1 more source

Visual-inertial direct SLAM

2016 IEEE International Conference on Robotics and Automation (ICRA), 2016
The so-called direct visual SLAM methods have shown a great potential in estimating a semidense or fully dense reconstruction of the scene, in contrast to the sparse reconstructions of the traditional feature-based algorithms. In this paper, we propose for the first time a direct, tightly-coupled formulation for the combination of visual and inertial ...
Alejo Concha, Giuseppe Loianno, Vijay Kumar, Javier Civera   +3 more
openaire   +1 more source

Light-SLAM: A Robust Deep-Learning Visual SLAM System Based on LightGlue Under Challenging Lighting Conditions

IEEE transactions on intelligent transportation systems (Print)
Simultaneous Localization and Mapping (SLAM) has become a critical technology for intelligent transportation systems and autonomous robots and is widely used in autonomous driving. However, traditional manual feature-based methods in challenging lighting
Zhiqi Zhao, Chang Wu, Xiao-jiang Kong, Qiyan Li, Zifan Guo, Zejie Lv, Xiaoqi Du   +6 more
semanticscholar   +1 more source

Unsupervised Monocular Depth Estimation for Monocular Visual SLAM Systems

IEEE Transactions on Instrumentation and Measurement
Estimating monocular depth and ego-motion via unsupervised learning has emerged as a promising approach in autonomous driving, mobile robots, and augmented reality (AR)/VR applications.
Feng Liu, Min Huang, Hongyu Ge, Dan Tao, Ruipeng Gao   +4 more
semanticscholar   +1 more source