The 100:100 Challenge for Computing in Rescue Robotics - Texas A&M University (TAMU) Scholar

Our vision of computing for rescue robotics is to achieve Metcalfe's Law sized effects, where the value of multiple heterogeneous robots (100) to diverse stakeholders (100) is proportional to the square of the connections. The more stakeholders who can access and use the data from more robots in real-time, the greater the expected value of robots to the emergency enterprise. This would shift the paradigm from the current state of the practice where a small set of operators and trained response professionals use robot data for local decisions to the desired state where many groups of remote stakeholders work directly with the data (both single source and aggregated) and may be unaware of the robotic source(s). The 100:100 Challenge encourages the computing community to continue existing research in increasing autonomy and mapping to help make the robots more reliable, easier to coordinate, and simplify data fusion and visualization; expand research in human-robot interaction and multi-robot coordination to engage new topics in remote presence, user interfaces, data visualization, training, remote manipulation, and victim management to make control of the robot to stakeholders; and incorporate existing lines of research in artificial intelligence (especially planning, scheduling, reasoning) and networking to provide complete and efficient multi-agent coordination and distribution of data. 2011 IEEE.

The 100:100 Challenge for Computing in Rescue Robotics Conference Paper