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Fastslam: A Scalable Method for the Simultaneous Localization and Mapping Problem in Robotics

Fastslam: A Scalable Method for the Simultaneous Localization and Mapping Problem in Robotics

          
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About the Book

This monograph, from the winners of the DARPA Grand Challenge, describes a new family of algorithms for the simultaneous localization and mapping problem in robotics (SLAM). It is the first book on the market about FastSLAM which is the most influential of recent contributions to the SLAM problem for mobile robots. 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 in the past few years, 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.


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Product Details
  • ISBN-13: 9783540463993
  • Publisher: Springer
  • Publisher Imprint: Springer
  • Depth: 13
  • Height: 239 mm
  • No of Pages: 120
  • Series Title: Springer Tracts in Advanced Robotics (Hardcover)
  • Sub Title: A Scalable Method for the Simultaneous Localization and Mapping Problem in Robotics
  • Width: 157 mm
  • ISBN-10: 3540463992
  • Publisher Date: 01 Mar 2007
  • Binding: Hardback
  • Edition: 2007 ed.
  • Language: English
  • Returnable: Y
  • Spine Width: 10 mm
  • Weight: 376 gr


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