CPS 300 - Graduate Seminar Student Presentations Mobile Robot Navigation with Neural Maps Michail G. Lagoudakis Department of Computer Science Duke University (Center for Advanced Computer Studies) (University of Southwestern Louisiana) Motivation Autonomous Robots – Planetary Exploration – Service Robots – Inspection Robots Biologically-Inspired Robots – Animal Learning and Behavior – Neural Network Models Talk Outline Background – Mobile Robot Navigation – Neural Maps Navigation with Neural Maps The Polar Neural Map Implementation on a Nomad 200 Results Conclusions Mobile Robots RWI B14 Nomad XR4000 RWI B21 Nomad 150 Nomad 200 Mobile Robot Navigation Global – Map-Based – Deliberative – Slow Local – Sensory-Based – Reactive – Fast Navigation Subproblems What should I remember? • Cognitive Mapping Where am I? • Localization Where should I go? • Path Planning How can I go? • Motion Control Animal Navigation Robot Navigation Navigation Landscape Neural Maps “A localized neural representation of signals in the outer world” [Amari] Hopfield-type Neural Networks Topologically Ordered Units Neural Map Property Amplification through Self-Organization Neurons Non-linear Processing Units ui (t) Wi V(t) i (t) Non-Linear Dynamics vi (t 1) (ui (t)) dvi (t) (ui (t)) vi (t) dt Path Planning with Neural Maps Network Topology Path Planning Example 1 Path Planning Example 1 Path Planning Example 1 Path Planning Example 2 Path Planning Example 2 Path Planning Example 2 Problem? Global Information? A “Bad” Idea A “Good” Idea The Polar Neural Map Represents the local space. Resembles the distribution of sensory data. Provides higher resolution closer to the robot. Conventions: – Inner Ring: Robot Center – Outer Ring: Target Direction Example Example (...continued) Example (...continued) Example (...continued) Boudreaux (Nomad 200) Nonholonomic Mobile Base Zero Gyro-Radius Max Speeds: 24 in/sec, 60 deg/sec Diameter: 21 in, Height: 31 in Pentium-Based Master PC Linux Operating System Full Wireless 1.6 Mbps Ethernet 16 Sonar Ring (6 in - 255 in) 20 Bump Sensors System Architecture Results Results (…continued) Results (…continued) Results (…continued) Results (…continued) Results (…continued) Robot Movie Enjoy some robotic video footage! Contributions Neural Maps for Fast Path Planning The Polar Neural Map Implementation on a Real Robot A Complete Local Navigation Scheme Future Work On-board Code Execution Polar and Logarithmic Map Global Navigation Neural Map Self-Organization More Information M.Sc. Thesis, Poster – http://www.cs.duke.edu/~mgl/acadpape.html IEEE ICRA ’99 Paper – Email: [email protected] Thank You The End! Special thanks to The Robotics and Automation Lab at USL Prof. Anthony S. Maida Prof. Kimon P. Valavanis Prof. Bill Z. Manaris ©1998 - CPS 300 Inc.