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Titlebook: Experimental Robotics I; The First Internatio Vincent Hayward,Oussama Khatib Conference proceedings 1990 Springer-Verlag Berlin Heidelberg

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書目名稱Experimental Robotics I
副標題The First Internatio
編輯Vincent Hayward,Oussama Khatib
視頻videohttp://file.papertrans.cn/319/318914/318914.mp4
叢書名稱Lecture Notes in Control and Information Sciences
圖書封面Titlebook: Experimental Robotics I; The First Internatio Vincent Hayward,Oussama Khatib Conference proceedings 1990 Springer-Verlag Berlin Heidelberg
描述The scope of this volume is to provide a forum dedicated to Experimental Robotics. The focus is on theoretical work which has been validated through experimental implementation. The papers are research papers pre- senting new results which reflect the conjecture-experimental cycle that researchers have gone through.
出版日期Conference proceedings 1990
關鍵詞Hidden Markov Model; actuator; autonom; control; filtering; kinematics; learning; linear optimization; mobil
版次1
doihttps://doi.org/10.1007/BFb0042509
isbn_softcover978-3-540-52182-2
isbn_ebook978-3-540-46917-9Series ISSN 0170-8643 Series E-ISSN 1610-7411
issn_series 0170-8643
copyrightSpringer-Verlag Berlin Heidelberg 1990
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Liste der Rezensionen zu [H 1972a]S operates under admittance control and can experimentally simulate a wide variety of linear and non-linear six-degree-of-freedom compliances. A series of experiments are described that use modelling of the base compliance and end point control to achieve precise positioning of the end effector of a
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An experimental system for incremental environment modelling by an autonomous mobile robot, consistent environment model and an as precise as possible robot positioning. The experimental system (a mobile robot with a laser range finder and odometry) is presented and the theoretical approach is applied on actual data.
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https://doi.org/10.1007/978-3-642-51317-6rithm is used for model based analysis of force signals measured during experimental teleoperation and achieves excellent segmentation of the data into sub-goal phases. The Hidden Markov Model achieves a structured, knowledge based model with explicit uncertainties and mature optimal identification algorithms.
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