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MIN Faculty Department of Informatics University of Hamburg RatSLAM: A Bio-inspired Approach to Robot Navigation RatSLAM: A Bio-inspired Approach to Robot Navigation Phil Bradfield University of Hamburg Faculty of Mathematics, Informatics

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University of Hamburg

MIN Faculty Department of Informatics RatSLAM: A Bio-inspired Approach to Robot Navigation

RatSLAM: A Bio-inspired Approach to Robot Navigation

Phil Bradfield

University of Hamburg Faculty of Mathematics, Informatics and Natural Sciences Department of Informatics Technical Aspects of Multimodal Systems

4. Januar 2016

Phil Bradfield 1

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University of Hamburg

MIN Faculty Department of Informatics RatSLAM: A Bio-inspired Approach to Robot Navigation

Outline

1. The SLAM Problem
2. SLAM in Biological Systems
3. RatSLAM
4. Results
5. Further Developments
6. Conclusion

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University of Hamburg

MIN Faculty Department of Informatics The SLAM Problem RatSLAM: A Bio-inspired Approach to Robot Navigation

The SLAM Problem

SLAM = Simultaneous Localisation and Mapping

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University of Hamburg

MIN Faculty Department of Informatics The SLAM Problem RatSLAM: A Bio-inspired Approach to Robot Navigation

The SLAM Problem

SLAM = Simultaneous Localisation and Mapping How can a mobile robot, dropped into a completely unknown environment:

◮ create an internal map of its environment... ◮ ...and identify its location within the map... ◮ ...at the same time?

Also known as the Kidnapped Robot Problem

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University of Hamburg

MIN Faculty Department of Informatics The SLAM Problem - Typical Approaches RatSLAM: A Bio-inspired Approach to Robot Navigation

The SLAM Problem - Typical Approaches

OpenSLAM.org

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University of Hamburg

MIN Faculty Department of Informatics The SLAM Problem - Typical Approaches RatSLAM: A Bio-inspired Approach to Robot Navigation

The SLAM Problem - Typical Approaches

OpenSLAM.org

◮ Open source implementations of 32 SLAM algorithms

Main categories:

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University of Hamburg

MIN Faculty Department of Informatics The SLAM Problem - Typical Approaches RatSLAM: A Bio-inspired Approach to Robot Navigation

The SLAM Problem - Typical Approaches

OpenSLAM.org

◮ Open source implementations of 32 SLAM algorithms

Main categories:

◮ (Extended) Kalman filter ◮ Particle filter ◮ Graph-based

Some good solutions in there... but none are perfect

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University of Hamburg

MIN Faculty Department of Informatics SLAM in Biological Systems RatSLAM: A Bio-inspired Approach to Robot Navigation

SLAM in Biological Systems

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University of Hamburg

MIN Faculty Department of Informatics SLAM in Biological Systems RatSLAM: A Bio-inspired Approach to Robot Navigation

SLAM in Biological Systems - Place Cells

◮ Located in the hippocampus ◮ Activate when the rat is at a specific location (“place field”)

Place cells in the hippocampus [1]

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University of Hamburg

MIN Faculty Department of Informatics SLAM in Biological Systems RatSLAM: A Bio-inspired Approach to Robot Navigation

SLAM in Biological Systems - Grid Cells

◮ Located in the endorhinal cortex ◮ Activate in a grid-like pattern

(a) Trajectory of a rat through a

square environment [5]

(b) Spatial autocorrelogram of the

neuronal activity of the grid cell [4]

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University of Hamburg

MIN Faculty Department of Informatics SLAM in Biological Systems RatSLAM: A Bio-inspired Approach to Robot Navigation

SLAM in Biological Systems - Head Direction Cells

◮ Located in various brain areas, including the thalamus ◮ Fire based on the direction the rat is facing ◮ Direction is absolute, not relative to the rat’s body

Head Direction Cells [2]

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University of Hamburg

MIN Faculty Department of Informatics SLAM in Biological Systems RatSLAM: A Bio-inspired Approach to Robot Navigation

SLAM in Biological Systems -

Some of the brain areas (probably) involved in navigation [10]

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University of Hamburg

MIN Faculty Department of Informatics RatSLAM RatSLAM: A Bio-inspired Approach to Robot Navigation

RatSLAM

Developed at Queensland University of Technology, Australia

◮ 2004: Original implementation ◮ 2013: OpenRatSLAM

◮ Two versions: ◮ Standalone C++ version ◮ ROS-integrated version ◮ https://openslam.org/openratslam.html ◮ https://github.com/davidmball/ratslam

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University of Hamburg

MIN Faculty Department of Informatics RatSLAM - Architecture RatSLAM: A Bio-inspired Approach to Robot Navigation

RatSLAM - Architecture

High-level architecture of the RatSLAM system [6]

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University of Hamburg

MIN Faculty Department of Informatics RatSLAM - Architecture RatSLAM: A Bio-inspired Approach to Robot Navigation

RatSLAM - Architecture

RatSLAM Architecture [3]

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University of Hamburg

MIN Faculty Department of Informatics RatSLAM - Architecture RatSLAM: A Bio-inspired Approach to Robot Navigation

RatSLAM - Architecture

◮ Local view cells

◮ Array of rate-coded cells representing visual scenes ◮ Array varies in size based on the number of landmarks

◮ Pose cell network

◮ Pose cells - combination of grid cells and head direction cells ◮ 3D continuous attractor network ◮ Excitatory connections to local neighbourhood ◮ Inhibitory connections to every other cell

◮ Experience map

◮ Graphical map of the environment ◮ Combines information from the other two modules

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University of Hamburg

MIN Faculty Department of Informatics Results - Suburb Mapping RatSLAM: A Bio-inspired Approach to Robot Navigation

Results - Suburb Mapping

Created map of 66km of roads from a single webcam feed

[7]

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University of Hamburg

MIN Faculty Department of Informatics Results - Suburb Mapping RatSLAM: A Bio-inspired Approach to Robot Navigation

Results - Suburb Mapping

[7]

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University of Hamburg

MIN Faculty Department of Informatics Results - Delivery Experiment RatSLAM: A Bio-inspired Approach to Robot Navigation

Results - Delivery Experiment

◮ Camera + odometry (+ IR sensors for collision avoidance) ◮ 1,143 “delivery tasks” ◮ 11 different locations ◮ 2 different buildings ◮ 37 hours of active operation ◮ 23 autonomous recharges ◮ Only 1 failed delivery

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University of Hamburg

MIN Faculty Department of Informatics Further Developments RatSLAM: A Bio-inspired Approach to Robot Navigation

Further Developments

◮ S¨

underhauf and Protzel (2010) [9]

◮ Analysed RatSLAM in comparison to Bayesian methods ◮ Developed a novel Bayesian filter based on the analysis

◮ M¨

uller, Weber and Wermter (2014) [8]

◮ Adapted RatSLAM to a humanoid robot

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University of Hamburg

MIN Faculty Department of Informatics Conclusion - Strengths RatSLAM: A Bio-inspired Approach to Robot Navigation

Conclusion - Strengths

◮ Reliable results using only very simple sensors ◮ Scalable to large spaces ◮ Stable over long time periods ◮ Neuroscience marches on...

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University of Hamburg

MIN Faculty Department of Informatics Conclusion - Weaknesses RatSLAM: A Bio-inspired Approach to Robot Navigation

Conclusion - Weaknesses

◮ Large open spaces can be a problem ◮ Very simplistic visual odometry ◮ Limited by pose cell network architecture ◮ Neuroscience marches on...

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University of Hamburg

MIN Faculty Department of Informatics Conclusion - Weaknesses RatSLAM: A Bio-inspired Approach to Robot Navigation

Thank you!

Questions?

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University of Hamburg

MIN Faculty Department of Informatics Conclusion - Weaknesses RatSLAM: A Bio-inspired Approach to Robot Navigation

References

[1] https://knowingneurons.files.wordpress.com/2013/04/place-cell-animation.gif. Retrieved 31/12/2015. [2] http://www.memoryspace.mvm.ed.ac.uk/images/head direction cells 3.png. Retrieved 31/12/2015. [3] David Ball, Scott Heath, Janet Wiles, Gordon Wyeth, Peter Corke, and Michael Milford. Openratslam: an open source brain-based slam system. Autonomous Robots, 34(3):149–176, 2013. [4] Torkel Hafting. Activity of a grid cell in rat (entorhinal cortex). https://commons.wikimedia.org/wiki/File:Autocorrelationplot grid cell.JPG, 2006. Retrieved 31/12/2015. [5] Torkel Hafting. Trajectory of a rat through a square environment. https://commons.wikimedia.org/wiki/File:RatRunningPath.JPG, 2006. Retrieved 31/12/2015.

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University of Hamburg

MIN Faculty Department of Informatics Conclusion - Weaknesses RatSLAM: A Bio-inspired Approach to Robot Navigation

References (cont.)

[6]

M. Milford.

Ratslam: Using models of rodent hippocampus for robot navigation. https://www.youtube.com/watch?v=t2w6kYzTbr8, August 2012. Retrieved 29/12/2015. [7] Michael Milford and Gordon Wyeth. Mapping a suburb with a single camera using a biologically inspired slam system. https://www.youtube.com/watch?v=-0XSUi69Yvs, January 2009. Retrieved 29/12/2015. [8] Stefan M¨ uller, Cornelius Weber, and Stefan Wermter. Ratslam on humanoids - a bio-inspired slam model adapted to a humanoid robot. In Stefan Wermter, Cornelius Weber, W lodzis law Duch, Timo Honkela, Petia Koprinkova-Hristova, Sven Magg, G¨ unther Palm, and AlessandroE.P. Villa, editors, Artificial Neural Networks and Machine Learning – ICANN 2014, volume 8681 of Lecture Notes in Computer Science, pages 789–796. Springer International Publishing, 2014.

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University of Hamburg

MIN Faculty Department of Informatics Conclusion - Weaknesses RatSLAM: A Bio-inspired Approach to Robot Navigation

References (cont.)

[9] Niko S¨ underhauf and Peter Protzel. Beyond ratslam: Improvements to a biologically inspired slam system. In Emerging Technologies and Factory Automation (ETFA), 2010 IEEE Conference on, pages 1–8, Sept 2010. [10] Jeffrey Taube. Head direction cells and the neurophysiological basis for a sense of direction. Progress in Neurobiology, 55(3):225 – 256, 1998.

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