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

TL;DR

This paper presents a robust, rapidly deployable autonomous aerial vehicle system designed for high-stakes real-world missions, emphasizing robustness, rapid deployment, and successful competition performance without reliance on central communication or RTK-GPS.

Contribution

It introduces a mission-structure-based robustness approach with outcome monitoring and recovery, enabling quick deployment and resilience in challenging outdoor environments.

Findings

Placed fourth in Challenge 2 and seventh in the Grand Challenge at MBZIRC 2020.

Successfully completed complex tasks like balloon popping, block manipulation, and fire extinguishing autonomously.

Demonstrated robustness and rapid deployment in real outdoor tests and international competition.

Abstract

For robotic systems to succeed in high risk, real-world situations, they have to be quickly deployable and robust to environmental changes, under-performing hardware, and mission subtask failures. These robots are often designed to consider a single sequence of mission events, with complex algorithms lowering individual subtask failure rates under some critical constraints. Our approach utilizes common techniques in vision and control, and encodes robustness into mission structure through outcome monitoring and recovery strategies. In addition, our system infrastructure enables rapid deployment and requires no central communication. This report also includes lessons in rapid field robotic development and testing. We developed and evaluated our systems through real-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 most water onto an outdoor, real fire with an autonomous UAV (Challenge 3).