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Design and Model Predictive Control of a Mars Coaxial Quadrotor
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0002-0020-6020
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0003-3557-6782
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0003-3922-1735
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0001-8870-6718
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2022 (English)In: 2022 IEEE Aerospace Conference (AERO), IEEE, 2022Conference paper, Published paper (Refereed)
Abstract [en]

Mars has been a prime candidate for planetary explo-ration of the solar system because of the science discoveries that support chances of future habitation on this planet. The Mars exploration landers and rovers have laid the foundation of our understanding of the planet's atmosphere and terrain. However, the rovers have presented limitations in terms of their pace, travers ability, and exploration capabilities from the ground and thus, one of the main field of interest for future robotic mission to Mars is to enhance the autonomy of this exploration vehicles. Martian caves and lava tubes like terrains, which consists of uneven ground, poor visibility and confined space, makes it impossible for wheel based rovers to navigate through these areas. In order to address these limitations and advance the exploration capability in a Martian terrain, this article presents the design and control of a novel coaxial quadrotor Micro Aerial Vehicle (MAV). As it will be presented, the key contributions on the design and control architecture of the proposed Mars coaxial quadrotor, are introducing an alternative and more enhanced, from a control point of view concept, when compared in terms of autonomy to Ingenuity. Based on the presented design, the article will introduce the mathematical modelling and automatic control framework of the vehicle that will consist of a linearised model of a co-axial quadrotor and a corresponding Model Pre-dictive Controller (MPC) for the trajectory tracking. Among the many models, proposed for the aerial flight on Mars, a reliable control architecture lacks in the related state of the art. The MPC based closed loop responses of the proposed MAV will be verified in different conditions during the flight with additional disturbances, induced to replicate a real flight scenario. For the model validation purpose, the Mars coaxial quadrotor is sim-ulated inside a Martian environment with related atmospheric conditions in the Gazebo simulator, which will use the proposed MPC controller for following an a priory defined trajectory. In order to further validate the proposed control architecture and prove the efficacy of the suggested design, the introduced Mars coaxial quadrotor and the MPC scheme will be compared to a PID-type controller, similar to the Ingenuity helicopter's control architecture for the position and the heading.

Place, publisher, year, edition, pages
IEEE, 2022.
National Category
Fusion, Plasma and Space Physics
Research subject
Robotics and Artificial Intelligence
Identifiers
URN: urn:nbn:se:ltu:diva-92649DOI: 10.1109/AERO53065.2022.9843799Scopus ID: 2-s2.0-85137574427OAI: oai:DiVA.org:ltu-92649DiVA, id: diva2:1689812
Conference
2022 IEEE Aerospace Conference (AERO), Big Sky, Montana, USA, March 5- 12, 2022
Note

ISBN för värdpublikation: 978-1-6654-3760-8 (digital)

Available from: 2022-08-24 Created: 2022-08-24 Last updated: 2023-04-19Bibliographically approved
In thesis
1. Towards Enabling Exploration of Planetary Subterranean Environments using Unmanned Aerial Vehicles
Open this publication in new window or tab >>Towards Enabling Exploration of Planetary Subterranean Environments using Unmanned Aerial Vehicles
2023 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis presents a novel navigation framework established to enable the exploration of planetary subterranean areas with Unmanned Aerial Vehicles (UAVs). The key contributions of this thesis work form a robot-safe rapid navigation framework that utilizes a novel bifurcating frontier-based exploration approach. UAVs (limited to quadrotors in this work) have superior navigation capabilities compared to ground robots in terms of 3D navigation as well as fast and versatile Traversability. Utilizing this advantage, this thesis investigates exploration and path-planning problems and presents novel mission behavior-oriented exploration strategies that are evaluated through either simulation with true physics and atmospheric models of planetary bodies or real-world deployment in subterranean areas.  The work included in this thesis is focused on two main research directions. The first direction establishes a novel coaxial quadrotor design that can operate in the thin atmosphere of Mars and utilize the Mars Coaxial Quadrotor (MCQ) to develop an energy-efficient exploration algorithm that leads to autonomously map Martian underground lava channel through true atmospheric model-based simulations. While the second direction establishes a Rapid Exploration Framework (REF) for the real-world deployment for the exploration of GPS-denied underground environments with UAVs. The contributions in the two directions are merged to develop a field-hardened autonomous exploration pipeline for UAVs that focuses on maintaining the heading vector of the UAV towards the most unknown area ahead of the UAV. While also bifurcating the exploration problem in local and global exploration for rapid navigation towards the unknown areas in the field of view and quickly globally re-positioning to a partially explored area. For navigating to the exploration goal of the UAV, it utilizes an expendable grid-based risk-aware path planning framework (D$^{*}_{+}$) that explicitly models unknown areas as risk and plans paths in safe space and for local obstacle avoidance and control the framework utilizes Artificial Potential Fields (APF) and a nonlinear Model Predictive Control based reference tracking scheme.Based on the learnings from field experiments and limitations of state-of-the-art grid-based planning methods on large-scale maps, the final contribution of the thesis establishes a Grid + Graph oriented Traversability-aware exploration and planning framework. The graph-based exploration method proposed in this thesis utilizes geometric shapes to define local traversable paths for the UAV to navigate to the local exploration goal. While utilizing a traversable graph that incrementally plans paths to the edge vertex of sub-maps in the direction of the global re-position goal. The strategy is evaluated extensively in simulations in subterranean urban, tunnel, and cave environments while it is also tested in real-world deployment at test mines of EPIROC and LKAB in Sweden.

Place, publisher, year, edition, pages
Luleå: Luleå University of Technology, 2023
Series
Licentiate thesis / Luleå University of Technology, ISSN 1402-1757
National Category
Robotics
Research subject
Robotics and Artificial Intelligence
Identifiers
urn:nbn:se:ltu:diva-96667 (URN)978-91-8048-317-9 (ISBN)978-91-8048-318-6 (ISBN)
Presentation
2023-06-15, A117, Luleå tekniska universitet, Luleå, 09:00 (English)
Opponent
Supervisors
Available from: 2023-04-19 Created: 2023-04-19 Last updated: 2023-05-25Bibliographically approved

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Patel, AkashBanerjee, AvijitLindqvist, BjörnKanellakis, ChristoforosNikolakopoulos, George

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