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Home ยป Using a Memory of Motion to Efficiently Warm-Start a Nonlinear Predictive Controller

Using a Memory of Motion to Efficiently Warm-Start a Nonlinear Predictive Controller

TitleUsing a Memory of Motion to Efficiently Warm-Start a Nonlinear Predictive Controller
Publication TypeConference Paper
Year of Publication2018
AuthorsMansard, N, Del Prete, A, Geisert, M, Tonneau, S, Stasse, O
Conference Name2018 IEEE International Conference on Robotics and Automation (ICRA)
Date PublishedMay
KeywordsApproximation algorithms, autonomous aerial vehicles, complex dynamical systems, Computational modeling, control cycle, control policy, direct optimal control, iterative methods, kinodynamic probabilistic roadmap, learning (artificial intelligence), model-based methodology, nonlinear control systems, nonlinear optimization problem, nonlinear predictive controller, nonlinear solver, optimal control, optimal state-control trajectories, optimisation, path planning, Planning, policy learning, Predictive control, Robots, sampling methods, sampling-based planning, trajectory optimisation (aerospace), Trajectory optimization, UAV, unmanned aerial vehicle
URLhttps://hal.archives-ouvertes.fr/hal-01591373
DOI10.1109/ICRA.2018.8463154
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