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A Newton method with always feasible iterates for Nonlinear Model Predictive Control of walking in a multi-contact situation

Diana Serra 1 Camille Brasseur 2 Alexander Sherikov 2 Dimitar Dimitrov 2 Pierre-Brice Wieber 2
2 BIPOP - Modelling, Simulation, Control and Optimization of Non-Smooth Dynamical Systems
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann , Grenoble INP [2007-2019] - Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019]
Abstract : In this paper, we present a Nonlinear Model Predictive Control scheme, which is able to generate walking motions in multi-contact situations. Walking up and down stairs with an additional hand support is a typical example, which we address in simulation. Computing such a nonlinear control scheme is usually done with a Newton method, a potentially time-consuming procedure involving iterative linearizations. We propose here a Newton method which is specifically designed to provide at each iteration a feasible solution, always satisfying the (nonlinear) dynamic balance constraints. This results in a significant reduction in computation time, by minimizing the number of necessary iterations to reach a feasible solution.
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https://hal.inria.fr/hal-01418402
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Submitted on : Friday, December 16, 2016 - 4:44:31 PM
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Diana Serra, Camille Brasseur, Alexander Sherikov, Dimitar Dimitrov, Pierre-Brice Wieber. A Newton method with always feasible iterates for Nonlinear Model Predictive Control of walking in a multi-contact situation. IEEE-RAS 2016 - International Conference on Humanoid Robots (Humanoids), Nov 2016, Cancun, Mexico. pp.932-937, ⟨10.1109/HUMANOIDS.2016.7803384⟩. ⟨hal-01418402⟩

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