Results 51 to 60 of about 3,501 (181)

Visual and Visual‐Inertial SLAM Based on Enhanced Deep Learning Features and Motion Smoothness Constraints

Advanced Intelligent Systems, EarlyView.
A visual and visual‐inertial simultaneous localization and mapping (SLAM) algorithm, leveraging enhanced deep learning features and motion smoothness constraints, is proposed in this research work. This method retains the advantages of geometry‐based SLAM methods while effectively utilizing the powerful representational capabilities of data‐driven ...
Maosheng Jiang, Lei Ma, Muhua Zhang, Kai Shen   +3 more
wiley   +1 more source

Visual SLAM for Unmanned Aerial Vehicles: Localization and Perception

Sensors
Localization and perception play an important role as the basis of autonomous Unmanned Aerial Vehicle (UAV) applications, providing the internal state of movements and the external understanding of environments.
Licong Zhuang, Xiaorong Zhong, Linjie Xu, Chunbao Tian, Wenshuai Yu   +4 more
doaj   +1 more source

An Attention-Based Odometry Framework for Multisensory Unmanned Ground Vehicles (UGVs)

Drones, 2023
Recently, deep learning methods and multisensory fusion have been applied to address odometry challenges in unmanned ground vehicles (UGVs). In this paper, we propose an end-to-end visual-lidar-inertial odometry framework to enhance the accuracy of pose ...
Zhiyao Xiao, Guobao Zhang
doaj   +1 more source

Virtual Elastic Tether: A New Approach for Multi‐Agent Navigation in Confined Aquatic Environments

Journal of Field Robotics, EarlyView.
ABSTRACT Underwater navigation is a challenging area in the field of mobile robotics due to inherent constraints in self‐localization and communication in underwater environments. Some of these challenges can be mitigated by using collaborative multi‐agent teams.
Kanzhong Yao, Xueliang Cheng, Keir Groves, Barry Lennox, Ognjen Marjanovic, Simon Watson   +5 more
wiley   +1 more source

Pseudo-LiDAR for Visual Odometry

IEEE Transactions on Instrumentation and Measurement, 2023
In the existing methods, LiDAR odometry shows superior performance, but visual odometry is still widely used for its price advantage. Conventionally, the task of visual odometry mainly rely on the input of continuous images. However, it is very complicated for the odometry network to learn the epipolar geometry information provided by the images.
Yanzi Miao, Huiying Deng, Chaokang Jiang, Zhiheng Feng, Xinrui Wu, Guangming Wang 0001, Hesheng Wang 0001   +6 more
openaire   +2 more sources

Representation Learning for Place Recognition Using MIMO Radar

IEEE Open Journal of Intelligent Transportation Systems
Traditional radar perception often rely on point clouds derived from radar heatmap using CFAR filtering, which can result in the loss of valuable information, especially weaker signals crucial for accurate perception.
Prashant Kumar Rai, Nataliya Strokina, Reza Ghabcheloo   +2 more
doaj   +1 more source

Deep Learning-Based Approach for Autonomous Vehicle Localization: Application and Experimental Analysis

Machines, 2023
In a vehicle, wheel speed sensors and inertial measurement units (IMUs) are present onboard, and their raw data can be used for localization estimation. Both wheel sensors and IMUs encounter challenges such as bias and measurement noise, which accumulate
Norbert Markó, Ernő Horváth, István Szalay, Krisztián Enisz   +3 more
doaj   +1 more source

Control System for the Navigation of the Agricultural Robots: A Review

Journal of Field Robotics, EarlyView.
ABSTRACT Control systems for the navigation of autonomous agricultural robots—particularly those operating in uneven terrain and in the presence of static or dynamic obstacles—have advanced considerably in recent years. As conventional machinery evolves toward increasingly automated systems, the design of reliable navigation controllers has become ...
Edna Carolina Moriones Polanía, Hugo Rafacho Fernandes, Daniel Albiero, Angel Pontin Garcia   +3 more
wiley   +1 more source

Extended Kalman Filter-Based 2D Pose Estimation for Omnidirectional Mecanum Robots via Sensor Fusion: A SO(2) Lie Group Formulation

Engineering Proceedings
This article presents a 2D pose estimation method for an omnidirectional mobile robot with Mecanum wheels, using an extended Kalman filter (EKF) formulated on the Lie group SO(2).
Dayanara Tata, William Chamorro, Diego Maldonado, Ronald Pillajo   +3 more
doaj   +1 more source

Trajectory Tracking pada Robot Omni dengan Metode Odometry

Jurnal Nasional Teknik Elektro dan Teknologi Informasi, 2019
This paper presents trajectory tracking on omni robots using odometry method. The odometry system aims to estimate the position relative to the initial position of the omni robot to estimate changes in position over time.
Fahmizal Fahmizal, Dhiya Uddin Rijalussalam, Maun Budiyanto, Afrizal Mayub   +3 more
doaj   +1 more source