Evo-ROS: Integrating evolution and the robot operating system
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.
Ardupilot, Autonomous vehicle, Evolutionary robotics, Fault tolerance, Gazebo, Robot Operating System, Sensor placement, Sonar
Simon, Glen A., Jared M. Moore, Anthony J. Clark, and Philip K. McKinley. "Evo-ROS: integrating evolution and the robot operating system." In Proceedings of the Genetic and Evolutionary Computation Conference Companion, pp. 1386-1393. 2018.
GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion