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- 2006936725 abstract "This monograph describes a new family of algorithms for the simultaneous localization and mapping problem in robotics (SLAM). SLAM addresses the problem of acquiring an environment map with a roving robot, while simultaneously localizing the robot relative to this map. This problem has received enormous attention in the robotics community, reaching a peak of popularity on the occasion of the DARPA Grand Challenge in October 2005, which was won by the team headed by the authors. The FastSLAM family of algorithms applies particle filters to the SLAM Problem, which provides new insights into the data association problem that is paramount in SLAM. The FastSLAM-type algorithms have enabled robots to acquire maps of unprecedented size and accuracy in a number of robot application domains and have been successfully applied in different dynamic environments, including the solution to the problem of people tracking.".
- 2006936725 contributor B10745623.
- 2006936725 contributor B10745624.
- 2006936725 created "c2007.".
- 2006936725 date "2007".
- 2006936725 date "c2007.".
- 2006936725 dateCopyrighted "c2007.".
- 2006936725 description "Includes bibliographical references (p. [111]-116) and index.".
- 2006936725 description "This monograph describes a new family of algorithms for the simultaneous localization and mapping problem in robotics (SLAM). SLAM addresses the problem of acquiring an environment map with a roving robot, while simultaneously localizing the robot relative to this map. This problem has received enormous attention in the robotics community, reaching a peak of popularity on the occasion of the DARPA Grand Challenge in October 2005, which was won by the team headed by the authors. The FastSLAM family of algorithms applies particle filters to the SLAM Problem, which provides new insights into the data association problem that is paramount in SLAM. The FastSLAM-type algorithms have enabled robots to acquire maps of unprecedented size and accuracy in a number of robot application domains and have been successfully applied in different dynamic environments, including the solution to the problem of people tracking.".
- 2006936725 extent "xiii, 119 p. :".
- 2006936725 identifier "3540463992".
- 2006936725 identifier "9783540463993".
- 2006936725 identifier 2006936725-d.html.
- 2006936725 identifier 2006936725-t.html.
- 2006936725 isPartOf "Springer tracts in advanced robotics ; v. 27".
- 2006936725 issued "2007".
- 2006936725 issued "c2007.".
- 2006936725 language "eng".
- 2006936725 publisher "Berlin : Springer,".
- 2006936725 subject "629.8/932 22".
- 2006936725 subject "Cartography.".
- 2006936725 subject "Data transmission systems.".
- 2006936725 subject "Mobile robots.".
- 2006936725 subject "Robots Control systems.".
- 2006936725 subject "TJ211.35 .M667 2007".
- 2006936725 title "FastSLAM : a scalable method for the simultaneous localization and mapping problem in robotics / Michael Montemerlo, Sebastian Thrun ; [foreword by Bruno Siciliano].".
- 2006936725 type "text".