Allocation for Omnidirectional Aerial Robots: Incorporating Power Dynamics

[2412.16107] Allocation for Omnidirectional Aerial Robots: Incorporating Power Dynamics Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Science > Robotics arXiv:2412.16107 (cs) [Submitted on 20 Dec 2024 ( v1 ), last revised 10 Apr 2026 (this version, v4)] Title: Allocation for Omnidirectional Aerial Robots: Incorporating Power Dynamics Authors: Eugenio Cuniato , Mike Allenspach , Thomas Stastny , Helen Oleynikova , Roland Siegwart , Michael Pantic View a PDF of the paper titled Allocation for Omnidirectional Aerial Robots: Incorporating Power Dynamics, by Eugenio Cuniato and 5 other authors View PDF HTML (experimental) Abstract: Tilt-rotor aerial robots are more dynamic and versatile than fixed-rotor platforms, since the thrust vector and body orientation are decoupled. However, the coordination of servos and propellers (the allocation problem) is not trivial, especially accounting for overactuation and actuator dynamics. We incrementally build and present three novel allocation methods for tilt-rotor aerial robots, comparing them to state-of-the-art methods on a real system performing dynamic maneuvers. We extend the state-of-the-art geometric allocation into a differential allocation, which uses the platform's redundancy and does not suffer from singularities. We expand it by incorporating actuator dynamics and propeller power dynamics. These allow us to model dynamic propeller acceleration limits, bringing two main advantages: balancing propeller speed without the need for nullspace goals and allowing the platform to selectively turn off propellers during flight, opening the door to new manipulation possibilities. We also use actuator dynamics and limits to normalize the allocation problem, making it easier to tune and allowing it to track 70% faster trajectories than a geometric allocation. Subjects: Robotics (cs.RO) Cite as: arXiv:2412.16107 [cs.RO] (or arXiv:2412.16107v4 [cs.RO] for this version) https://doi.org/10.48550/arXiv.2412.16107 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Eugenio Cuniato [ view email ] [v1] Fri, 20 Dec 2024 17:48:56 UTC (8,139 KB) [v2] Thu, 31 Jul 2025 12:32:27 UTC (9,377 KB) [v3] Wed, 21 Jan 2026 12:12:22 UTC (9,372 KB) [v4] Fri, 10 Apr 2026 11:15:14 UTC (9,372 KB) Full-text links: Access Paper: View a PDF of the paper titled Allocation for Omnidirectional Aerial Robots: Incorporating Power Dynamics, by Eugenio Cuniato and 5 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.RO < prev | next > new | recent | 2024-12 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from

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