New Robotics and Automation Findings from University of Toronto Described (Toward Certifying Maps for Safe Registration-based Lo- calization Under Adverse Conditions)

Robotics & Machine Learning Daily News2024，Issue(Feb.27) ：47-47.DOI:10.1109/LRA.2023.3346751

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IEEE

New Robotics and Automation Findings from University of Toronto Described (Toward Certifying Maps for Safe Registration-based Lo- calization Under Adverse Conditions)

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Abstract

2024 FEB 27 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Robotics - Robotics and Automation are presented in a new report. According to news reporting originating from Toronto, Canada, by NewsRx correspondents, research stated, “In this letter, we propose a way to model the resilience of the Iterative Closest Point (ICP) algorithm in the presence of corrupted measurements. In the context of autonomous vehicles, certifying the safety of the localization process poses a significant challenge.” Financial support for this research came from CGIAR.

Key words

Toronto/Canada/North and Central America/Robotics and Automation/Robotics/University of Toronto

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出版年

2024

Robotics & Machine Learning Daily News

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参考文献量24

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