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Whole-Body Real-Time Motion Planning for Multicopters
KTH, School of Electrical Engineering and Computer Science (EECS). State Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou, 310027, China.
Zhejiang Univ, Inst Cyber Syst & Control, State Key Lab Ind Control Technol, Hangzhou 310027, Peoples R China.;Nanjing Inst Technol, Sch Automat, Nanjing 211112, Peoples R China..
Zhejiang Univ, Inst Cyber Syst & Control, State Key Lab Ind Control Technol, Hangzhou 310027, Peoples R China..
Zhejiang Univ, Inst Cyber Syst & Control, State Key Lab Ind Control Technol, Hangzhou 310027, Peoples R China.;Zhejiang Univ, Huzhou Inst, Huzhou 313000, Peoples R China..
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2021 (English)In: 2021 IEEE International Conference on Robotics and Automation (ICRA), Institute of Electrical and Electronics Engineers (IEEE) , 2021, p. 9197-9203Conference paper, Published paper (Refereed)
Abstract [en]

Multicopters are able to perform high maneuverability yet their potential have not been fully achieved. In this work, we propose a full-body, optimization-based motion planning framework that takes shape and attitude of aerial robot into consideration such that the aggressiveness of drone maneuvering improves significantly in cluttered environment. Our method takes in a series of intersecting polyhedrons that describe a range of 3D free spaces and outputs a time-indexed trajectory in real-time with full-body collision-free guarantee. The drone is modeled as a tilted cuboid, yet we argue that our framework can be freely adjusted to fit multicopters of different shapes. Guaranteeing dynamic feasibility and safety conditions, our framework transforms the original constrained nonlinear programming problem to an unconstrained one in higher dimensions which is further solved by quasi-Newton methods. Benchmark has shown that our method improves the state-of-art with orders of magnitude in terms of computation time and memory usage. Simulations and onboard experiments are carried out as validation.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2021. p. 9197-9203
Series
IEEE International Conference on Robotics and Automation ICRA, ISSN 1050-4729
National Category
Robotics and automation
Identifiers
URN: urn:nbn:se:kth:diva-311660DOI: 10.1109/ICRA48506.2021.9561526ISI: 000771405402056Scopus ID: 2-s2.0-85125479089OAI: oai:DiVA.org:kth-311660DiVA, id: diva2:1655617
Conference
IEEE International Conference on Robotics and Automation (ICRA), May 30-JUN 05, 2021, Xian, China
Note

Part of proceedings: ISBN 978-1-7281-9077-8

QC 20220503

Available from: 2022-05-03 Created: 2022-05-03 Last updated: 2025-02-09Bibliographically approved

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