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Silin Zhao

dblp:304/4266 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Robot navigation and mapping · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot navigation and mapping › mobile robot navigation › sensor-based navigation
magnetic navigation
0.512021
An Improved Magnetic Spot Navigation for Replacing the Barcode Navigation in Automated Guided Vehicles · ICRA 2021
Robotics › Robot navigation and mapping › localization › robot localization
mobile robot localization
0.512021
An Improved Magnetic Spot Navigation for Replacing the Barcode Navigation in Automated Guided Vehicles · ICRA 2021
Robotics › Robot navigation and mapping › localization
odometry
0.112021
An Improved Magnetic Spot Navigation for Replacing the Barcode Navigation in Automated Guided Vehicles · ICRA 2021

Methods — techniques the papers use, named apart from their topics

adaptive weighted fusion · 0.5
YearPublicationVenuePosition
2021 An Improved Magnetic Spot Navigation for Replacing the Barcode Navigation in Automated Guided Vehicles
abstract
The barcode navigation based on QR (quick response) codes is widely employed in industrial logistics due to its accurate localization and flexible movement paths. However, the regular repair of damaged barcodes and robot speed control when approaching the barcodes are required. In this study, we presented an improved magnetic spot navigation approach to replace the barcode navigation for automated guided vehicles (AGVs). The fusion of the high-precision magnetic tracking method and odometer based on AGV encoders can overcome the disadvantages of barcode navigation. The magnetic tracking approach provides the AGV pose relative to the nearest magnet spot, instead of the low-precision longitudinal and lateral measurement via a magnetic ruler. Besides, with the benefit of the adaptive weighted fusion algorithm, the distance between the adjacent barcode can be set from 500 to 1000 mm via magnetic spots. Experimental results show that the mean path accuracy and mean magnet spot localization accuracy of the improved magnetic spot navigation were 110 ± 30 mm and 14.5 ± 0.87 mm, respectively. The proposed approach provides a novel possibility for large-area and high-precision navigation in AGVs-based industrial logistics, especially for large outdoor scenarios.
Houde Dai, Silin Zhao, Penghua Liu, Guijuan Lin
ICRA4