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

In English

Författare

  • 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.

Publiceringsår

2014

Språk

Engelska

Dokumenttyp

Konferensbidrag

Ämne

  • 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

Forskningsgrupp

  • LCCC
  • ELLIIT