首页|New Robotics and Automation Findings from University of Toronto Described (Toward Certifying Maps for Safe Registration-based Lo- calization Under Adverse Conditions)
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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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.
TorontoCanadaNorth and Central AmericaRobotics and AutomationRoboticsUniversity of Toronto
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