Team NimbRo's UGV Solution for Autonomous Wall Building and Fire Fighting at MBZIRC 2020

TL;DR

This paper describes NimbRo's fully autonomous UGV system designed for complex tasks like wall building and fire fighting, evaluated during the MBZIRC 2020 competition, highlighting its integrated hardware, perception, and planning capabilities.

Contribution

The paper introduces a comprehensive autonomous UGV system with integrated hardware and software for complex tasks, demonstrating successful competition performance and providing insights into system design and operation.

Findings

Successfully participated in MBZIRC 2020 finals

Achieved autonomous wall construction and fire extinguishing

Provided valuable lessons learned for future robotic systems

Abstract

Autonomous robotic systems for various applications including transport, mobile manipulation, and disaster response are becoming more and more complex. Evaluating and analyzing such systems is challenging. Robotic competitions are designed to benchmark complete robotic systems on complex state-of-the-art tasks. Participants compete in defined scenarios under equal conditions. We present our UGV solution developed for the Mohamed Bin Zayed International Robotics Challenge 2020. Our hard- and software components to address the challenge tasks of wall building and fire fighting are integrated into a fully autonomous system. The robot consists of a wheeled omnidirectional base, a 6 DoF manipulator arm equipped with a magnetic gripper, a highly efficient storage system to transport box-shaped objects, and a water spraying system to fight fires. The robot perceives its environment using 3D LiDAR as well as RGB and thermal camera-based perception modules, is capable of picking box-shaped objects and constructing a pre-defined wall structure, as well as detecting and localizing heat sources in order to extinguish potential fires. A high-level planner solves the challenge tasks using the robot skills. We analyze and discuss our successful participation during the MBZIRC 2020 finals, present further experiments, and provide insights to our lessons learned.