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Rao-Blackwellized Particle Smoothing for Occupancy-Grid Based SLAM Using Low-Cost Sensors

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Author

  • Karl Berntorp
  • Jerker Nordh

Summary, in English

We approach the simultaneous localization and mapping problem by using an ultrasound sensor and wheel encoders on a mobile robot. The measurements are modeled to yield a conditionally linear model for all the map states. Moreover, we implement a Rao-Blackwellized particle smoother (RBPS) for jointly estimating the position of the robot and the map. The method is applied and successfully verified by experiments on a small Lego robot where ground truth was obtained by the use of a VICON real-time positioning system. The results show that the RBPS contributes with more robust estimates at the cost of computational complexity and memory usage.

Publishing year

2014

Language

English

Document type

Conference paper

Topic

  • Control Engineering

Conference name

19th IFAC World Congress, 2014

Conference date

2014-08-24 - 2014-08-29

Conference place

Cape Town, South Africa

Status

Published

Research group

  • LCCC
  • ELLIIT