Least conservative linearized constraint formulation for real-time motion generation

Abstract: Today robotics has shown many successful strategies to solve several navigation problems. However, moving into a dynamic environment is still a challenging task. This paper presents a novel method for motion generation in dynamic environments based on real-time nonlinear model predictive control (NMPC). At the core of our approach is a least conservative linearized constraint formulation built upon the real-time iteration (RTI) scheme with Gauss-Newton Hessian approximation. We demonstrate that the proposed constraint formulation is less conservative for planners based on Newton-type method than for those based on a fully converged NMPC method. Additionally, we show the performance of our approach in simulation, in a scenario where the Crazyflie nanoquadcopter avoids balls and reaches its desired goal in spite of the uncertainty about when the balls will be thrown. The numerical results validate our theoretical findings and illustrate the computational efficiency of the proposed scheme

Standort
Deutsche Nationalbibliothek Frankfurt am Main
Umfang
Online-Ressource
Sprache
Englisch
Anmerkungen
IFAC-PapersOnLine. - 53, 2 (2020) , 9384-9390, ISSN: 2405-8963

Klassifikation
Zeitschriften, fortlaufende Sammelwerke

Ereignis
Veröffentlichung
(wo)
Freiburg
(wer)
Universität
(wann)
2025
Urheber
Carlos, Bárbara Barros
Sartor, Tommaso
Zanelli, Andrea
Diehl, Moritz
Oriolo, Giuseppe
Beteiligte Personen und Organisationen

DOI
10.1016/j.ifacol.2020.12.2407
URN
urn:nbn:de:bsz:25-freidok-2618529
Rechteinformation
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Letzte Aktualisierung
15.08.2025, 07:34 MESZ

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  • 2025

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