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For robotic systems to succeed in high risk, real-world situations, they haveto be quickly deployable and robust to environmental changes, under-performinghardware, and mission subtask failures. These robots are often designed toconsider a single sequence of mission events, with complex algorithms loweringindividual subtask failure rates under some critical constraints. Our approachutilizes common techniques in vision and control, and encodes robustness intomission structure through outcome monitoring and recovery strategies. Inaddition, our system infrastructure enables rapid deployment and requires nocentral communication. This report also includes lessons in rapid field roboticdevelopment and testing. We developed and evaluated our systems throughreal-robot experiments at an outdoor test site in Pittsburgh, Pennsylvania,USA, as well as in the 2020 Mohamed Bin Zayed International Robotics Challenge.All competition trials were completed in fully autonomous mode without RTK-GPS.Our system placed fourth in Challenge 2 and seventh in the Grand Challenge,with notable achievements such as popping five balloons (Challenge 1),successfully picking and placing a block (Challenge 2), and dispensing the mostwater onto an outdoor, real fire with an autonomous UAV (Challenge 3).

Mission-level Robustness with Rapidly-deployed, Autonomous Aerial Vehicles by Carnegie Mellon Team Tartan at MBZIRC 2020