An Implementation of Artificial Physics Using AIBO Robots and the Pyro Programming Environment Ankur Desai December 7, 2006

Naval Research Laboratories Artificial Intelligence Center 4555 Overlook Ave., SW Washington, DC 20375

Mitchell A. Potter, Ph.D. Principal Investigator Evolutionary Robotics Coevolutionary Models Representation Issues Continuous and Embedded Learning

Adaptive Systems Team Shared lab space Variety of robotic equipment No wireless communications Upcoming anniversary demonstration

Rationale Divide tasks between multiple robots Based on natural behaviors Unified platforms

Purpose Determine whether AIBO is an effective platform for artificial physics Create Python module to control the AIBO robots

Artificial Physics Developed by Spears and Gordon in 1999 Each robot treated as a molecule Gravitational forces simulated

Artificial Physics Grid formationResource protection

Sony AIBO

Python Robotics Interpreted language Platform-blind High-level control

Testing Design Straight line accuracy Turning accuracy Correct functioning of simulation No testing necessary

Materials Software SWIG Tekkotsu Pyro Seven AIBO robots

Procedures – Python module Build C library object files Create SWIG wrapper Compile wrapper into dynamic library

Procedures – Odometry Setup Place AIBO in empty room Connect to host computer Send command Walk 10 meters Turn 360° Measure actual motion

Straight Line Results

Turning Results

Conclusion Python module successful AIBO is not a suitable platform Alternate localization techniques Use of different robotic models

Reflections Overall positive experience Delayed security clearance Limited wireless access Difficult commute

Acknowledgments I would like to thank the Adaptive Systems team at Naval Research Laboratories Artificial Intelligence Center, especially Mitchell Potter and R. Paul Wiegand, for their guidance and support throughout this project.

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