The MRS UAV System: Pushing the Frontiers of Reproducible Research, Real-world Deployment, and Education with Autonomous Unmanned Aerial Vehicles (2008.08050v5)

Abstract: We present a multirotor Unmanned Aerial Vehicle control (UAV) and estimation system for supporting replicable research through realistic simulations and real-world experiments. We propose a unique multi-frame localization paradigm for estimating the states of a UAV in various frames of reference using multiple sensors simultaneously. The system enables complex missions in GNSS and GNSS-denied environments, including outdoor-indoor transitions and the execution of redundant estimators for backing up unreliable localization sources. Two feedback control designs are presented: one for precise and aggressive maneuvers, and the other for stable and smooth flight with a noisy state estimate. The proposed control and estimation pipeline are constructed without using the Euler/Tait-Bryan angle representation of orientation in 3D. Instead, we rely on rotation matrices and a novel heading-based convention to represent the one free rotational degree-of-freedom in 3D of a standard multirotor helicopter. We provide an actively maintained and well-documented open-source implementation, including realistic simulation of UAV, sensors, and localization systems. The proposed system is the product of years of applied research on multi-robot systems, aerial swarms, aerial manipulation, motion planning, and remote sensing. All our results have been supported by real-world system deployment that shaped the system into the form presented here. In addition, the system was utilized during the participation of our team from the CTU in Prague in the prestigious MBZIRC 2017 and 2020 robotics competitions, and also in the DARPA SubT challenge. Each time, our team was able to secure top places among the best competitors from all over the world. On each occasion, the challenges has motivated the team to improve the system and to gain a great amount of high-quality experience within tight deadlines.

Overview of the MRS UAV System

The paper "The MRS UAV System: Pushing the Frontiers of Reproducible Research, Real-world Deployment, and Education with Autonomous Unmanned Aerial Vehicles" presents an innovative platform for the control and estimation of multirotor UAVs. The MRS UAV system is designed to support reproducible research through realistic simulation environments and real-world experimental capabilities. This paper details the system's architecture, which enables diverse UAV missions in both GNSS-enabled and GNSS-denied scenarios, with particular attention given to transitions between indoor and outdoor environments. Fundamental to the system is a novel multi-frame localization paradigm that supports state estimation across various coordinate frames using multiple sensors.

This paper delineates two distinct feedback control designs: one optimized for precise and aggressive maneuvers and the other tailored for stable flights when state estimates are impacted by noise. These designs circumvent traditional Euler/Tait-Bryan angle representations by using rotation matrices, thereby simplifying the representation of orientation in 3D and enhancing the control's effectiveness over the UAVs' degrees of freedom.

Numerical Results and Claims

The MRS UAV system's efficacy is evidenced by the real-world deployment in prestigious robotics competitions such as MBZIRC 2017/2020 and the DARPA Subterranean Challenge, where the system's robust design enabled the team to secure top positions. Furthermore, the control pipeline's versatility allows for both aggressive flight patterns with acceleration limits up to \SI{12}{\meter\per\second\squared} and stable flights under noisy conditions, showcasing the system's adaptability and reliability.

Major Contributions

Key contributions of the system include a robust framework for handling multiple sensory inputs through a bank of filters, each maintaining its hypothesis within different frames. This framework ensures that seamless transitions occur when switching estimators, offering flexibility in uncertain environments. Additionally, the open-source nature of the system facilitates collaboration and further research by making a sophisticated UAV control system accessible to the wider research community. The paper emphasizes the importance of modularity, allowing users to integrate and test novel control methods easily.

The comprehensive implementation of the system on the Robot Operating System (ROS) and the inclusion of a realistic simulation environment ensures that researchers can transition smoothly from simulation to real-world deployments. This modular approach extends to the future developments of UAV platforms, encouraging further refinement and application across various domains.

Implications and Future Developments

The MRS UAV system sets a precedent for future developments in autonomous aerial systems by emphasizing the integration of reproducible research methodologies with practical, real-world applications. The dual control designs and the modularity of the system offer significant value to research in UAV swarming, autonomous navigation in GNSS-denied environments, and aerial manipulation tasks. As the field of UAV technologies continues to advance, future developments may look towards enhancing AI-driven decision-making and further sensor integration to improve autonomous capabilities and robustness under dynamic environmental conditions.

In summary, this paper contributes a significant step forward in UAV research by offering a detailed, open-platform control system that balances precision with robustness, supporting both fundamental research and practical applications in the field of robotics. The strategic use of multi-frame localization and innovative control designs positions the MRS UAV system as a foundational tool for ongoing and future research in aerial robotics.