Inside the Virtual Robotics Challenge: Simulating Real-Time Robotic Disaster Response

Inside the Virtual Robotics Challenge: Simulating Real-Time Robotic Disaster Response This paper presents the software framework established to facilitate cloud-hosted robot simulation. The framework addresses the challenges associated with conducting a task-oriented and real-time robot competition, the Defense Advanced Research Projects Agency (DARPA) Virtual Robotics Challenge (VRC), designed to mimic reality. The core of the framework is the Gazebo simulator, a platform to simulate robots, objects, and environments, as well as the enhancements made for the VRC to maintain a high fidelity simulation using a high degree of freedom and multisensor robot. The other major component used is the CloudSim tool, designed to enhance the automation of robotics simulation using existing cloud technologies. The results from the VRC and a discussion are also detailed in this work. Note to Practitioners – Advances in robot simulation, cloud hosted infrastructure, and web technology have made it possible to accurately and efficiently simulate complex robots and environments on remote servers while providing realistic data streams for human-in-the-loop robot control. This paper presents the software and hardware frameworks established to facilitate cloud-hosted robot simulation, and addresses the challenges associated with conducting a task-oriented robot competition designed to mimic reality. The competition that spurred this innovation was the VRC, a precursor to the DARPA Robotics Challenge, in which teams from around the world utilized custom human-robot interfaces and control code to solve disaster response-related tasks in simulation. Winners of the VRC received both funding and access to Atlas, a humanoid robot developed by Boston Dynamics. The Gazebo simulator, an open source and high fidelity robot simulator, was improved upon to met the needs of the VRC competition. Additionally, CloudSim was created to act as an interface between users and the cloud-hosted simulations. As a result of this work, we have achieved automated deployment of cloud resources f- r robotic simulations, near real-time simulation performance, and simulation accuracy that closely mimics real hardware. These tools have been released under open source licenses and are freely available, and can be used to help reduce robot and algorithm design and development time, and increase robot software robustness.