The published paper can be found here, on the Field Robotics website. We present the following contributions:
strategies for simple, yet robust algorithms in computer vision, vision-based control and guidance, and mission planning;
an autonomous system-startup and mission-launching architecture that facilitates the rapid deployment of our robots in time-constrained and WiFi-denied settings;
show that mission plans containing self-check cycles helped us overcome faulty hardware and failed subtasks and still succeed in the overall mission;
thorough assessments of failure cases at MBZIRC 2020 and describe critical lessons learned from field development and testing.
In the supplement, we present work done beyond the competition: a post-competition simulation analysis of our ball-catching strategy and the development and assessment of a better control strategy, and a real-world UAV-UGV cooperative block stacking strategy.
Feel free to contact Anish Bhattacharya with any questions! This is a collaboration between the AirLab and the Intelligent Autonomous Manipulation Lab.