The use of robots in complex tasks such as search and rescue operations is becoming more and more common. These robots often work independently with no cooperation with other robots or control software, and are very limited in their ability to perform dynamic tasks and interact with both humans and other robots. To this end, a system must be developed to facilitate the cooperation of heterogeneous robots to complete complex tasks. To model and study human-robot and robot-robot interactions in a multi-system environment, a robust network infrastructure must be implemented to support the broad nature of these studies. The work presented here details the creation of a cloud-based infrastructure designed to support the introduction and implementation of multiple heterogeneous robots to the environment utilizing the Robot Operating System (ROS). Implemented robots include both ground-based (e.g. Turtlebot) and air-based (e.g Parrot ARDrone2.0) systems. Additional hardware is also implemented, such as embedded vision systems, host computers to support virtual machines for software implementation, and machines with graphics processing units (GPUs) for additional computational resources. Control software for the robots is implemented in the system with complexities ranging from simple teleoperation to skeletal tracking and neural network simulators. A robust integration of multiple heterogeneous components, including both hardware and software, is achieved.

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