Evolutionary Robotics on the Web with WebGL and Javascript

by   Jared Moore, et al.
Michigan State University

Web-based applications are highly accessible to users, providing rich, interactive content while eliminating the need to install software locally. However, evolutionary robotics (ER) has faced challenges in this domain as web-based technologies have not been amenable to 3D physics simulations. Traditionally, physics-based simulations require a local installation and a high degree of user knowledge to configure an environment, but the emergence of Javascript-based physics engines enables complex simulations to be executed in web browsers. These developments create opportunities for ER research to reach new audiences by increasing accessibility. In this work, we introduce two web-based tools we have built to facilitate the exchange of ideas with other researchers as well as outreach to K-12 students and the general public. The first tool is intended to distribute and exchange ER research results, while the second is a completely browser-based implementation of an ER environment.



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  • Bongard et al. [2012] Josh Bongard, Paul Beliveau, and Gregory Hornby. Avoiding local optima with interactive evolutionary robotics. In

    Proceedings of the 14th Annual Conference Companion on Genetic and Evolutionary Computation

    , GECCO ’12, pages 1405–1406, Philadelphia, Pennsylvania, USA, 2012. ACM.
  • Cabello et al. [2014] Ricardo Cabello, Paul Brunt, Branislav Ulicny, and Joshua Koo. Threejs. http://threejs.org/, June 2014.
  • Clune and Lipson [2011] Jeff Clune and Hod Lipson. Evolving 3d objects with a generative encoding inspired by developmental biology. SIGEVOlution, 5(4):2–12, November 2011.
  • Coumans [2014] Erwin Coumans. Bullet physics engine. http://bulletphysics.org/wordpress/, June 2014.
  • Group [2014] Khronos Group. Webgl. http://www.khronos.org/webgl/, June 2014.
  • Prall [2014] Chandler Prall. Physijs. http://chandlerprall.github.io/Physijs/, April 2014.
  • Secretan et al. [2008] Jimmy Secretan, Nicholas Beato, David B. D Ambrosio, Adelein Rodriguez, Adam Campbell, and Kenneth O. Stanley. Picbreeder: Evolving pictures collaboratively online. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pages 1759–1768, Florence, Italy, 2008. ACM.
  • Sims [1994] Karl Sims. Evolving 3D morphology and behavior by competition. Artificial Life, 1(4):353–372, 1994. ISSN 1064-5462.