{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/157197"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/157197","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"State and Dynamics Estimation in an Outdoor Multi-Drone Slung Load System","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_html":"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_has_math":false,"creators":["Merton, Harvey"],"institution":"Massachusetts Institute of Technology","degree_name":"Master","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Mechanical Engineering","school":null,"contributors":[],"advisors":["Hunter, Ian W."],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-09","date_published":"2024-09","updated_at":"2026-07-22T22:22:29Z","subjects":[],"languages":[],"rights":["Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","Copyright retained by author(s)"],"rights_urls":["https://creativecommons.org/licenses/by-nc-nd/4.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1721.1/157197","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Hunter, Ian W."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Department of Mechanical Engineering"]},{"key":"dc:creator","label":"Author","values":["Merton, Harvey"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2024-10-09T18:27:40Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2024-10-09T18:27:40Z"]},{"key":"dc:date.issued","label":"Date","values":["2024-09"]},{"key":"dc:publisher","label":"Institution","values":["Massachusetts Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master","Master of Science in Mechanical Engineering"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","Copyright retained by author(s)"]},{"key":"dc:rights.uri","label":"Rights URI","values":["https://creativecommons.org/licenses/by-nc-nd/4.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/1721.1/157197"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["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."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M."]},{"key":"dc:title","label":"Title","values":["State and Dynamics Estimation in an Outdoor Multi-Drone Slung Load System"]}]}],"canonical_facts":{"dc:contributor.advisor":["Hunter, Ian W."],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Mechanical Engineering"],"dc:creator":["Merton, Harvey"],"dc:date.accessioned":["2024-10-09T18:27:40Z"],"dc:date.available":["2024-10-09T18:27:40Z"],"dc:date.issued":["2024-09"],"dc:description.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."],"dc:description.degree":["S.M."],"dc:identifier.uri":["https://hdl.handle.net/1721.1/157197"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","Copyright retained by author(s)"],"dc:rights.uri":["https://creativecommons.org/licenses/by-nc-nd/4.0/"],"dc:title":["State and Dynamics Estimation in an Outdoor Multi-Drone Slung Load System"],"dc:type":["Thesis"],"thesis:degree_name":["Master","Master of Science in Mechanical Engineering"]},"updated_at":"2026-07-22T22:22:29Z"}