4.6 Article

RGB-D Visual SLAM Based on Yolov4-Tiny in Indoor Dynamic Environment

Related references

Note: Only part of the references are listed.
Article Computer Science, Information Systems

Fast stereo visual odometry based on LK optical flow and ORB-SLAM2

Chuanye Tang et al.

Summary: A stereo visual odometry algorithm, LK-ORB-SLAM2, was proposed which combines optical flow tracking and feature matching to improve efficiency. Experimental results showed that LK-ORB-SLAM2 reduced processing time by about 70% while maintaining an accuracy change of less than 2%.

MULTIMEDIA SYSTEMS (2022)

Article Computer Science, Artificial Intelligence

Semantic visual SLAM in dynamic environment

Shuhuan Wen et al.

Summary: This study proposes a new SLAM method that utilizes mask R-CNN to detect dynamic objects in the environment and build a semantic map, effectively separating dynamic and static points and achieving geometric segmentation of dynamic objects, outperforming current state-of-the-art SLAM algorithms in experimental testing.

AUTONOMOUS ROBOTS (2021)

Article Computer Science, Information Systems

An Improved Light-Weight Traffic Sign Recognition Algorithm Based on YOLOv4-Tiny

Lanmei Wang et al.

Summary: By improving the K-means clustering algorithm, proposing a large-scale feature map optimization strategy, and an improved NMS algorithm, the accuracy, recall rate, and real-time performance of the traffic sign recognition algorithm based on YOLOv4-Tiny have been successfully improved.

IEEE ACCESS (2021)

Article Computer Science, Information Systems

RDMO-SLAM: Real-Time Visual SLAM for Dynamic Environments Using Semantic Label Prediction With Optical Flow

Yubao Liu et al.

Summary: vSLAM, a fundamental technology for augmented reality and intelligent mobile robots, has made progress in recent years through the use of neural networks and semantic information. The newly proposed RDMO-SLAM combines more semantic information, ensuring real-time performance by predicting semantic labels using dense optical flow.

IEEE ACCESS (2021)

Article Computer Science, Artificial Intelligence

Enhancing optical-flow-based control by learning visual appearance cues for flying robots

G. C. H. E. de Croon et al.

Summary: Researchers have proposed a new method for robots to estimate distances between objects by their visual appearance, which has been successfully implemented on a small flying robot. This approach results in improved performance in tasks such as landing and obstacle avoidance.

NATURE MACHINE INTELLIGENCE (2021)

Article Robotics

Humanoid Robot RGB-D SLAM in the Dynamic Human Environment

Tianwei Zhang et al.

INTERNATIONAL JOURNAL OF HUMANOID ROBOTICS (2020)

Article Computer Science, Artificial Intelligence

A Binocular MSCKF-Based Visual Inertial Odometry System Using LK Optical Flow

Guangqiang Li et al.

JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS (2020)

Article Computer Science, Information Systems

DDL-SLAM: A Robust RGB-D SLAM in Dynamic Environments Combined With Deep Learning

Yongbao Ai et al.

IEEE ACCESS (2020)

Article Computer Science, Information Systems

Semantic SLAM With More Accurate Point Cloud Map in Dynamic Environments

Yingchun Fan et al.

IEEE ACCESS (2020)

Article Computer Science, Information Systems

Dynamic Scene Semantics SLAM Based on Semantic Segmentation

Shuangquan Han et al.

IEEE ACCESS (2020)

Article Environmental Sciences

A New RGB-D SLAM Method with Moving Object Detection for Dynamic Indoor Scenes

Runzhi Wang et al.

REMOTE SENSING (2019)

Article Automation & Control Systems

Dynamic-SLAM: Semantic monocular visual localization and mapping based on deep learning in dynamic environment

Linhui Xiao et al.

ROBOTICS AND AUTONOMOUS SYSTEMS (2019)

Article Computer Science, Theory & Methods

Visual SLAM and Structure from Motion in Dynamic Environments: A Survey

Muhamad Risqi U. Saputra et al.

ACM COMPUTING SURVEYS (2018)

Article Robotics

DynaSLAM: Tracking, Mapping, and Inpainting in Dynamic Scenes

Berta Bescos et al.

IEEE ROBOTICS AND AUTOMATION LETTERS (2018)

Article Computer Science, Information Systems

Semantic SLAM Based on Object Detection and Improved Octomap

Liang Zhang et al.

IEEE ACCESS (2018)

Article Automation & Control Systems

Improving RGB-D SLAM in dynamic environments: A motion removal approach

Yuxiang Sun et al.

ROBOTICS AND AUTONOMOUS SYSTEMS (2017)