Geometric Approach to Mapping and Localization

Features:

  • Based on a abstract, compact representation of shape
  • Utilizes state-of-the-art shape matching
  • No odometry information required
  • Reliable & Efficient
  • Well-suited for object tracking and mapping applications

 

Principles of Operation:

  1. Shape features are extracted from laser range finder (LRF) data
  2. Shapes of two consecutive scans are matched against each other yielding a correspondence of objects
  3. A map of robot environment composed of just a few polylines is built incrementally
    by merging polylines in a local scan with the existing global map

 

Demonstration videos:

Indoor environment at the University of Bremen:

View movie (measure 2) illustrating our incremental map building

View shape-based feature tracking
 

 

Simulated environment with noise added:

 

View movie illustrating our incremental map building

 

This project was supported by NSF under the grant INT-0331786 (08/01/03-07/31/05) entitled
Robot Localization and Robot Mapping Based on Shape Matching
as US-Germany Cooperative Research between Temple University and the University of Bremen, Germany

and by a grant NIST 70NANB5H11119 (06/01/05-08/31/06) entitled 

Geometric Robot Mapping

from the National Institute of Standards and Technology. 
PI: Longin Jan Latecki

Collaborators:

Rolf Lakaemper (Temple University)

Diedrich Wolter and Christian Freksa (University of Bremen, Germany)

Xinyu Sun (Texas A&M University)