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20092022
most citedGuSTO: Guaranteed Sequential Trajectory Optimization via Sequential Convex Programming

119 citations · 355 across the 60 of their papers we have counts for

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Showing 2019 · math.OCShow all

5 papers · 2 filters

math.OC2019

Learning Stabilizable Nonlinear Dynamics with Contraction-Based Regularization

Sumeet Singh, Spencer M. Richards, Vikas Sindhwani +2

We propose a novel framework for learning stabilizable nonlinear dynamical systems for continuous control tasks in robotics. The key contribution is a control-theoretic regularizer…

math.OC2019

High-Dimensional Optimization in Adaptive Random Subspaces

Jonathan Lacotte, Mert Pilanci, Marco Pavone

We propose a new randomized optimization method for high-dimensional problems which can be seen as a generalization of coordinate descent to random subspaces. We show that an adapt…

math.OC201926 cited

Trajectory Optimization on Manifolds: A Theoretically-Guaranteed Embedded Sequential Convex Programming Approach

Riccardo Bonalli, Andrew Bylard, Abhishek Cauligi +2

Sequential Convex Programming (SCP) has recently gained popularity as a tool for trajectory optimization due to its sound theoretical properties and practical performance. Yet, mos…

math.OC2019

Scalable and Congestion-aware Routing for Autonomous Mobility-on-Demand via Frank-Wolfe Optimization

Kiril Solovey, Mauro Salazar, Marco Pavone

We consider the problem of vehicle routing for Autonomous Mobility-on-Demand (AMoD) systems, wherein a fleet of self-driving vehicles provides on-demand mobility in a given environ…

math.OC2019119 cited

GuSTO: Guaranteed Sequential Trajectory Optimization via Sequential Convex Programming

Riccardo Bonalli, Abhishek Cauligi, Andrew Bylard +1

Sequential Convex Programming (SCP) has recently seen a surge of interest as a tool for trajectory optimization. However, most available methods lack rigorous performance guarantee…