{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/mathcal-l-1-adaptive-augmentation-for","title":"$\\mathcal{L}_1$ Adaptive Augmentation for Geometric Tracking Control of Quadrotors","arxiv_id":"2109.06998","date":"2021-09-14","proceeding":null,"authors":["Zhuohuan Wu","Sheng Cheng","Kasey A. Ackerman","Aditya Gahlawat","Arun Lakshmanan","Pan Zhao","Naira Hovakimyan"],"abstract":"This paper introduces an $\\mathcal{L}_1$ adaptive control augmentation for geometric tracking control of quadrotors. In the proposed design, the $\\mathcal{L}_1$ augmentation handles nonlinear (time- and state-dependent) uncertainties in the quadrotor dynamics without assuming or enforcing parametric structures, while the baseline geometric controller achieves stabilization of the known nonlinear model of the system dynamics. The $\\mathcal{L}_1$ augmentation applies to both the rotational and the translational dynamics. Experimental results demonstrate that the augmented geometric controller shows consistent and (on average five times) smaller trajectory tracking errors compared with the geometric controller alone when tested for different trajectories and under various types of uncertainties/disturbances.","url_abs":"https://arxiv.org/abs/2109.06998v2","url_pdf":"https://arxiv.org/pdf/2109.06998v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"mathcal-l-1-adaptive-augmentation-for","repo_url":"https://github.com/HovakimyanResearch/L1-Mambo/blob/main/README.md","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null},{"paper_slug":"mathcal-l-1-adaptive-augmentation-for","repo_url":"https://github.com/hovakimyanresearch/l1-mambo","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}