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oai:dspace.mit.edu:1721.1/1571972024-10-10T03:01:16Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023

Hunter, Ian W. Merton, Harvey Massachusetts Institute of Technology. Department of Mechanical Engineering 2024-10-09T18:27:40Z 2024-10-09T18:27:40Z 2024-09 2024-09-25T15:57:17.299Z https://hdl.handle.net/1721.1/157197 https://orcid.org/0000-0002-3843-6868 Over the past decade, aerial drones have been used to address problems in areas such as sensing and measurement, inspection, delivery, security, and defense. Adding a load attached to one or more drones using a flexible cable can significantly enhance the capabilities of these platforms. This work aims to develop a multi-drone platform, built on open-source tools such as PX4 and ROS2, that can be used to lift a general slung load in an outdoor environment. Various fidelity simulators, including a pseudo-photo-realistic Gazebo simulator, are developed alongside a functional real world platform for testing load pose estimation methods. A novel cable-based testing apparatus that enables drone translation is used to facilitate stability testing of a quasi-static formation control method for lifting a slung load. This work aims to be the first to use visual feedback to estimate a load’s pose in a multi-drone slung load system operating without external motion capture devices. In simulation, perspective-n-point-based visual estimation achieves position errors of 0.1 m, and geodesic distance attitude errors around 0 ◦ . Real world testing shows errors of 0.2 m and 5 ◦ respectively. Applying extended Kalman filter and unscented Kalman filter formulations, simulated position estimates average around an error of 0 m, while the error noise magnitude is only 6% of the cable length at 0.06 m. Achieving accurate load pose estimates without an inertial measurement unit mounted to the load requires a good cable dynamics model. This work concludes by presenting a novel model for the effect of cables in a drone-slung-load system. A method based on universal differential equations shows promising early results. S.M. Massachusetts Institute of Technology Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) Copyright retained by author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/ State and Dynamics Estimation in an Outdoor Multi-Drone Slung Load System Thesis application/pdf Master Master of Science in Mechanical Engineering Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="f7f1c58a-cc1c-4322-9440-1768f1fb1f55"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Title>State and Dynamics Estimation in an Outdoor Multi-Drone Slung Load System</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2024-09</PublicationDate> <Authors> <Author> <DisplayName>Merton, Harvey</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>https://creativecommons.org/licenses/by-nc-nd/4.0/</License> <Abstract>Over the past decade, aerial drones have been used to address problems in areas such as sensing and measurement, inspection, delivery, security, and defense. Adding a load attached to one or more drones using a flexible cable can significantly enhance the capabilities of these platforms. This work aims to develop a multi-drone platform, built on open-source tools such as PX4 and ROS2, that can be used to lift a general slung load in an outdoor environment. Various fidelity simulators, including a pseudo-photo-realistic Gazebo simulator, are developed alongside a functional real world platform for testing load pose estimation methods. A novel cable-based testing apparatus that enables drone translation is used to facilitate stability testing of a quasi-static formation control method for lifting a slung load. This work aims to be the first to use visual feedback to estimate a load’s pose in a multi-drone slung load system operating without external motion capture devices. In simulation, perspective-n-point-based visual estimation achieves position errors of 0.1 m, and geodesic distance attitude errors around 0 ◦ . Real world testing shows errors of 0.2 m and 5 ◦ respectively. Applying extended Kalman filter and unscented Kalman filter formulations, simulated position estimates average around an error of 0 m, while the error noise magnitude is only 6% of the cable length at 0.06 m. Achieving accurate load pose estimates without an inertial measurement unit mounted to the load requires a good cable dynamics model. This work concludes by presenting a novel model for the effect of cables in a drone-slung-load system. A method based on universal differential equations shows promising early results.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>