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., SWWashington, DC 20375

Mitchell A. Potter, Ph.D.

Principal Investigator

Evolutionary RoboticsCoevolutionary ModelsRepresentation IssuesContinuous 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 formation Resource protection

Sony AIBO

Python Robotics

Interpreted language

Platform-blind

High-level control

Testing Design

Straight line accuracy

Turning accuracy

Correct functioning of simulationNo testing necessary

Materials

SoftwareSWIGTekkotsuPyro

Seven AIBO robots

Procedures – Python module

Build C library object files

Create SWIG wrapper

Compile wrapper into dynamic library

Procedures – OdometrySetup

Place AIBO in empty roomConnect to host computer

Send commandWalk 10 metersTurn 360°

Measure actual motion

Straight Line Results

0

2

4

6

8

10

12

Accuracy of Straight Line Odometry

WalkCrawl

Trial

Dis

tan

ce (

m)

Accuracy of Straight Line Odometry Data

10 9.44 -5.6 9.86 -1.410 4.7 -53 10.92 9.210 6.04 -39.6 5.68 -43.210 10.46 4.6 9.14 -8.610 5.24 -47.6 7.46 -25.410 10.7 7 3.6 -6410 9.42 -5.8 10.68 6.810 4.8 -52 10.42 4.210 6.5 -35 7.22 -27.810 4.24 -57.6 9.9 -1

Expected (meters)

Measured Walking (m)

Error (%)

Measured Crawling (m)

Error (%)

Turning Results

0

50

100

150

200

250

300

350

400

450

Accuracy of Turning Odometry

WalkCrawl

Trial

An

gle

(°)

Accuracy of Turning Odometry Data

Error (%) Error (%)360 220 -38.89 320 -11.11360 340 -5.56 250 -30.56360 190 -47.22 230 -36.11360 390 8.33 170 -52.78360 360 0 400 11.11360 330 -8.33 260 -27.78360 340 -5.56 390 8.33360 380 5.56 220 -38.89360 230 -36.11 340 -5.56360 360 0 190 -47.22

Expected (degrees)

Measured Walking (°)

Measured Crawling (°)

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.

Literature CitedBlank, D., Meeden, L., & Kumar, D. (2003). Python robotics: An environment for exploring robotics beyond LEGOs. SIGSCE ’03, 35, 317-3121.Ikemoto, Y., Hasegawa, Y., Fukuda, T., & Matsuda, K. (2005). Gradual spatial pattern formation of homogeneous robot group. Information Sciences, 171, 431-445.Lee, M. (2003). Evolution of behaviors in autonomous robot using artificial neural network and genetic algorithm. Information Sciences, 155, 43-60.Oliveira, E., Fischer, K., & Stepankova, O. (1999). Multi-agent systems: Which research for which applications. Robotics and Autonomous Systems, 27, 91- 106.Röfer, T., & Jüngel, M. (2003). Fast and robust edge-based localization in the Sony four-legged robot league. In Polani, D., Browning, B., Bonarini, A., & Yoshida, K. (Eds.), RoboCup 2003: Robot soccer world cup VII (pp. 262-273). Berlin: Springer.Spears, W. M., & Gordon, D. F. (1999). Using artificial physics to control agents. 1999 International Conference on Information Intelligence and Systems, 1999, 281- 288.Tira-Thompson, E. J., Halelamien, N. S., Wales, J. J., & Touretzky, D. S. (2004). Tekkotsu: Cognitive robotics on the Sony AIBO. Proceedings of the Sixth International Conference on Cognitive Modeling, 6, 390-391.