Results 91 to 100 of about 23,972 (233)

Efficient and Accurate Downfacing Visual–Inertial Odometry

open access: yesIEEE Internet of Things Journal
Visual Inertial Odometry (VIO) is a widely used computer vision method that determines an agent's movement through a camera and an IMU sensor. This paper presents an efficient and accurate VIO pipeline optimized for applications on micro- and nano-UAVs. The proposed design incorporates state-of-the-art feature detection and tracking methods (SuperPoint,
Jonas Kühne   +3 more
openaire   +2 more sources

An Integrated Algorithm Fusing UWB Ranging Positioning and Visual–Inertial Information for Unmanned Vehicles

open access: yesRemote Sensing
During the execution of autonomous tasks within sheltered space environments, unmanned vehicles demand highly precise and seamless continuous positioning capabilities.
Shuang Li   +6 more
doaj   +1 more source

Why Autonomous Vehicles Are Not Ready Yet: A Multi‐Disciplinary Review of Problems, Attempted Solutions, and Future Directions

open access: yesJournal of Field Robotics, Volume 43, Issue 3, Page 2254-2341, May 2026.
ABSTRACT Personal autonomous vehicles can sense their surrounding environment, plan their route, and drive with little or no involvement of human drivers. Despite the latest technological advancements and the hopeful announcements made by leading entrepreneurs, to date no personal vehicle is approved for road circulation in a “fully” or “semi ...
Xingshuai Dong   +13 more
wiley   +1 more source

Metric Localization using Google Street View

open access: yes, 2015
Accurate metrical localization is one of the central challenges in mobile robotics. Many existing methods aim at localizing after building a map with the robot.
Agarwal, Pratik   +2 more
core   +1 more source

Terrain Classification for Planetary Rovers Using Wireless In‐Wheel Sensor Modules and Machine Learning

open access: yesJournal of Field Robotics, Volume 43, Issue 3, Page 1884-1904, May 2026.
ABSTRACT Safe and reliable mobility over different kinds of ground is important for planetary rovers on space missions. Since terrain changes might affect the mobility of the rover, energy consumption, and safety, detecting the type of ground in real‐time is vital.
Md Masrul Khan   +7 more
wiley   +1 more source

Incremental Visual-Inertial 3D Mesh Generation with Structural Regularities

open access: yes, 2019
Visual-Inertial Odometry (VIO) algorithms typically rely on a point cloud representation of the scene that does not model the topology of the environment. A 3D mesh instead offers a richer, yet lightweight, model.
Carlone, Luca   +3 more
core   +1 more source

Asynchronous Visual-Inertial Odometry for Event Cameras [PDF]

open access: yesThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Event cameras are bio-inspired visual sensors that output changes in pixel-level brightness asynchronously instead of standard intensity frames at a fixed rate.
P. Li, H. Yao, Z. Dai, X. Zhu
doaj   +1 more source

Voxel‐SLAM: A Complete, Accurate, and Versatile Light Detection and Ranging‐Inertial Simultaneous Localization and Mapping System

open access: yesAdvanced Intelligent Systems, Volume 8, Issue 4, April 2026.
: In this work, Voxel‐SLAM (simultaneous localization and mapping) is introduced: a complete, accurate, and versatile LiDAR (light detection and ranging) ‐inertial SLAM system consisting of five modules: initialization, odometry, local mapping (LM), loop closure (LC), and global mapping (GM), all employing the same map representation, an adaptive voxel
Zheng Liu   +9 more
wiley   +1 more source

The Event-Camera Dataset and Simulator: Event-based Data for Pose Estimation, Visual Odometry, and SLAM

open access: yes, 2017
New vision sensors, such as the Dynamic and Active-pixel Vision sensor (DAVIS), incorporate a conventional global-shutter camera and an event-based sensor in the same pixel array.
Delbruck, Tobi   +4 more
core   +1 more source

ADVIO: An Authentic Dataset for Visual-Inertial Odometry [PDF]

open access: yes, 2018
The lack of realistic and open benchmarking datasets for pedestrian visual-inertial odometry has made it hard to pinpoint differences in published methods. Existing datasets either lack a full six degree-of-freedom ground-truth or are limited to small spaces with optical tracking systems.
Santiago Cortés   +3 more
openaire   +2 more sources

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