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Evo-ROS: integrating evolution and the robot operating system

Published:06 July 2018Publication History

ABSTRACT

In this paper, we describe the Evo-ROS framework, which is intended to help bridge the gap between the evolutionary and traditional robotics communities. Evo-ROS combines an evolutionary algorithm with individual physics-based evaluations conducted using the Robot Operating System (ROS) and the Gazebo simulation environment. Our goals in developing Evo-ROS are to (1) provide researchers in evolutionary robotics with access to the extensive support for real-world components and capabilities developed by the ROS community and (2) enable ROS developers, and more broadly robotics researchers, to take advantage of evolutionary search during design and testing. We describe the details of the Evo-ROS structure and operation, followed by presentation of a case study using Evo-ROS to optimize placement of sonar sensors on unmanned ground vehicles that can experience reduced sensing capability due to component failures and physical damage. The case study provides insights into the current capabilities and identifies areas for future enhancements.

References

  1. ArduPilot. Developer website, http://ardupilot.org/about, 2018. Online; accessed 31 January 2018.Google ScholarGoogle Scholar
  2. ArduPilot Dev Team. Auto Mode, http://ardupilot.org/copter/docs/auto-mode.html, 2016. Online; accessed 30 January 2018.Google ScholarGoogle Scholar
  3. K. Balakrishnan and V. Honavar. On sensor evolution in robotics. In Proceedings of the 1st Annual Conference on Genetic Programming, pages 455--460, Stanford, California, 1996. MIT Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. J. Bongard, V. Zykov, and H. Lipson. Resilient machines through continuous self-modeling. Science, 17, November 2006.Google ScholarGoogle Scholar
  5. J. C Bongard, A. Bernatskiy, K. Livingston, N. Livingston, J. Long, and M. Smith. Evolving robot morphology facilitates the evolution of neural modularity and evolvability. In Proceedings of the 2015 Genetic and Evolutionary Computation Conference, pages 129--136, Madrid, Spain, 2015. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Buyval, Alex. Aurélien, Roy. Maxime, Lafleur. Ardupilot SITL Gazebo Plugin. https://github.com/AurelienRoy/ardupilot_sitl_gazebo_plugin/tree/master/ardupilot_sitl_gazebo_plugin, 2015. Online; accessed 31 January 2018.Google ScholarGoogle Scholar
  7. A. J. Clark. Evolving Adabot: A mobile robot with adjustable wheel extensions. In 2017 IEEE Symposium Series on Computational Intelligence (SSCI), pages 1--8, Honolulu, HI, USA, 2017.Google ScholarGoogle ScholarCross RefCross Ref
  8. A. J. Clark, X. Tan, and P. K. McKinley. Evolutionary multiobjective design of a flexible caudal fin for robotic fish. Bioinspiration & Biomimetics, special issue on Bioinspired Soft Robotics, 10(6), November 2015.Google ScholarGoogle Scholar
  9. A. Cully, J. Clune, and J. Mouret. Robots that can adapt like natural animals. ArXiv Preprint, 2014.Google ScholarGoogle Scholar
  10. D. Duckworth, B. Shrewsbury, and R. Murphy. Run the robot backward. In 2013 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), pages 1--6. IEEE, 2013.Google ScholarGoogle ScholarCross RefCross Ref
  11. Erie Robotics. Erie-Rover, http://erlerobotics.com/blog/erle-rover/, 2018. Online; accessed 31 January 2018.Google ScholarGoogle Scholar
  12. Erie Robotics. Simulation Introduction, http://docs.erlerobotics.com/simulation/intro, 2018. Online; accessed 31 January 2018.Google ScholarGoogle Scholar
  13. D. Floreano, P. Husbands, and S. Nolfi. Evolutionary Robotics. In Handbook of Robotics. Springer Verlag, Berlin, 2008.Google ScholarGoogle ScholarCross RefCross Ref
  14. N. Koenig and A. Howard. Design and use paradigms for gazebo, an open-source multi-robot simulator, 04 2004.Google ScholarGoogle Scholar
  15. S. Koos, J. B. Mouret, and S. Doncieux. Crossing the reality gap in evolutionary robotics by promoting transferable controllers. In Proceedings of the 2010 ACM Genetic and Evolutionary Computation Conference, pages 119--126, Portland, Oregon, USA, 2010. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. H. Lipson and J. B. Pollack. Automatic design and manufacture of robotic lifeforms. Nature, 406(6799):974--978, August 2000.Google ScholarGoogle Scholar
  17. J. M. Moore and P. K. McKinley. Evolution of joint-level control for quadrupedal locomotion. Artificial Life, 23(1):58--79, January 2017. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. M. J. Rose, A. J. Clark, J. M. Moore, and P. K. McKinley. Just keep swimming: Accounting for uncertainty in self-modeling aquatic robots. In Proceedings of the 6th International Workshop on Evolutionary and Reinforcement Learning for Autonomous Robot Systems, Taormina, Italy, September 2013.Google ScholarGoogle Scholar
  19. F. Silva, M. Duarte, L. Correia, S. M. Oliveira, and. A. L. Christensen. Open issues in evolutionary robotics. Evolutionary Computation, 24(2):205--236, 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Tim Smith. About ROS. http://www.ros.Org/about-ros/t, 2018. Online; accessed 31 January 2018.Google ScholarGoogle Scholar
  21. X. Wang, S. X. Yang, W. Shi, and M. Q. H. Meng. A co-evolution approach to sensor placement and control design for robot obstacle avoidance. In 2004 International Conference on Information Acquisition, pages 107--112, Hefei, China, 2004.Google ScholarGoogle ScholarCross RefCross Ref
  22. Y. Zhang and J. Jiang. Bibliographical review on reconfigurable fault-tolerant control systems. Annual reviews in control, 32(2):229--252, 2008.Google ScholarGoogle Scholar

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