OpenRatSLAM: an open source brain-based SLAM system

  • Authors:

  • David Ball;Scott Heath;Janet Wiles;Gordon Wyeth;Peter Corke;Michael Milford

  • Affiliations:

  • School of Electrical Engineering and Computer Science, Queensland University of Technology, Brisbane, Australia;School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia;School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia;School of Electrical Engineering and Computer Science, Queensland University of Technology, Brisbane, Australia;School of Electrical Engineering and Computer Science, Queensland University of Technology, Brisbane, Australia;School of Electrical Engineering and Computer Science, Queensland University of Technology, Brisbane, Australia

  • Venue:
  • Autonomous Robots
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

RatSLAM is a navigation system based on the neural processes underlying navigation in the rodent brain, capable of operating with low resolution monocular image data. Seminal experiments using RatSLAM include mapping an entire suburb with a web camera and a long term robot delivery trial. This paper describes OpenRatSLAM, an open-source version of RatSLAM with bindings to the Robot Operating System framework to leverage advantages such as robot and sensor abstraction, networking, data playback, and visualization. OpenRatSLAM comprises connected ROS nodes to represent RatSLAM's pose cells, experience map, and local view cells, as well as a fourth node that provides visual odometry estimates. The nodes are described with reference to the RatSLAM model and salient details of the ROS implementation such as topics, messages, parameters, class diagrams, sequence diagrams, and parameter tuning strategies. The performance of the system is demonstrated on three publicly available open-source datasets.