Robust Mapping and Localization in Indoor Environments Using Sonar Data  

Oleh:

Tardós, Juan D. ; Neira, Jose ; Newman, Paul M. ; Leonard, John J.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: The International Journal of Robotics Research vol. 21 no. 4 (Apr. 2002), page 311-330.
Topik: map building; local maps; data association; sonar sensors; Hough transform
Fulltext: 311.pdf (763.98KB)

Isi artikel

In this paper we describe a new technique for the creation of featurebased stochastic maps using standard Polaroid sonar sensors. The fundamental contributions of our proposal are: (1) a perceptual grouping process that permits the robust identification and localization of environmental features, such as straight segments and corners, from the sparse and noisy sonar data; (2) a map joining technique that allows the system to build a sequence of independent limited-size stochastic maps and join them in a globally consistent way; (3) a robust mechanism to determine which features in a stochastic map correspond to the same environment feature, allowing the system to update the stochastic map accordingly, and perform tasks such as revisiting and loop closing. We demonstrate the practicality of this approach by building a geometric map of a medium size, real indoor environment, with several people moving around the robot. Maps built from laser data for the same experiment are provided for comparison.

Opini Anda

Klik untuk menuliskan opini Anda tentang koleksi ini!

Kembali