The ETH-MAV Team in the MBZ International Robotics Challenge

TL;DR

This paper details ETH Zurich's MAV systems for the 2017 MBZIRC, highlighting their integrated hardware-software design, autonomous capabilities, and successful competition results including rapid autonomous landing and high success rates in object pickup.

Contribution

It presents a comprehensive system architecture for outdoor MAVs, integrating computer vision, sensor fusion, and control, with experimental validation in a competitive environment.

Findings

Secured second place in Challenge 3 and Grand Challenge

Achieved autonomous landing in under one minute

Over 90% success rate in visual servoing for object pickup

Abstract

This article describes the hardware and software systems of the Micro Aerial Vehicle (MAV) platforms used by the ETH Zurich team in the 2017 Mohamed Bin Zayed International Robotics Challenge (MBZIRC). The aim was to develop robust outdoor platforms with the autonomous capabilities required for the competition, by applying and integrating knowledge from various fields, including computer vision, sensor fusion, optimal control, and probabilistic robotics. This paper presents the major components and structures of the system architectures, and reports on experimental findings for the MAV-based challenges in the competition. Main highlights include securing second place both in the individual search, pick, and place task of Challenge 3 and the Grand Challenge, with autonomous landing executed in less than one minute and a visual servoing success rate of over 90% for object pickups.