首页|Researchers from University of Verona Report New Studies and Findings in the Are a of Robotics (Minimum-energy Switching Geometric Filter On Lie Groups for Diffe rential-drive Wheeled Mobile Robots)
Researchers from University of Verona Report New Studies and Findings in the Are a of Robotics (Minimum-energy Switching Geometric Filter On Lie Groups for Diffe rential-drive Wheeled Mobile Robots)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News-A new study on Robotics is now availab le. According to news reporting from Verona,Italy, by NewsRx journalists, resea rch stated, "Accurate state estimation plays a critical role in variousapplicat ions, such as tracking, regulation, and fault detection in robotic and mechanica l systems. Typically,the Kalman-Bucy filter is used as a linear state observer for this purpose."The news correspondents obtained a quote from the research from the University o f Verona, "However,real-world robots often exhibit complex behavior, characteri zed by a combination of dynamics, makingit essential to employ hybrid filters. In this context, the Switching Kalman filter stands out as a wellestablishedso lution. In this article we aim to generalize the Brownian-Markov Stochastic Mode l, a hybriddynamic model for differential-drive wheeled mobile robots, to the c ase of a mobile robot whose centerof mass is not aligned to the wheels axle mid dle point, and to design a geometric hybrid state estimatorby exploiting the Li e groups theory. The Brownian-Markov Stochastic Model features two modes: ‘grip'and ‘slip'. These modes correspond to ideal grip and lateral slippage, with tra nsitions governed by astate-dependent Markov chain."
VeronaItalyEuropeEmerging Technolo giesMachine LearningNano-robotRobotRoboticsUniversity of Verona
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