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04/25/2023
Direct Collocation Methods for Trajectory Optimization in Constrained Robotic Systems
Direct collocation methods are powerful tools to solve trajectory optimi...
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04/03/2023
Imitation Learning from Nonlinear MPC via the Exact Q-Loss and its Gauss-Newton Approximation
This work presents a novel loss function for learning nonlinear Model Pr...
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12/22/2022
Frenet-Cartesian Model Representations for Automotive Obstacle Avoidance within Nonlinear MPC
In recent years, nonlinear model predictive control (NMPC) has been exte...
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12/06/2022
Safe Imitation Learning of Nonlinear Model Predictive Control for Flexible Robots
Flexible robots may overcome the industry's major problems: safe human-r...
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12/03/2022
A Hierarchical Approach for Strategic Motion Planning in Autonomous Racing
We present an approach for safe trajectory planning, where a strategic t...
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10/23/2022
Active Learning of Discrete-Time Dynamics for Uncertainty-Aware Model Predictive Control
Model-based control requires an accurate model of the system dynamics fo...
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11/20/2020
Convergence Analysis of Homotopy-SGD for non-convex optimization
First-order stochastic methods for solving large-scale non-convex optimi...
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10/21/2020
An Efficient Real-Time NMPC for Quadrotor Position Control under Communication Time-Delay
The advances in computer processor technology have enabled the applicati...
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06/12/2020
Kernel Distributionally Robust Optimization
This paper is an in-depth investigation of using kernel methods to immun...
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06/03/2020
On the Promise of the Stochastic Generalized Gauss-Newton Method for Training DNNs
Following early work on Hessian-free methods for deep learning, we study...
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03/31/2020
Worst-Case Risk Quantification under Distributional Ambiguity using Kernel Mean Embedding in Moment Problem
In order to anticipate rare and impactful events, we propose to quantify...
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01/28/2020
A Kernel Mean Embedding Approach to Reducing Conservativeness in Stochastic Programming and Control
We apply kernel mean embedding methods to sample-based stochastic optimi...
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01/15/2020
CIAO^: MPC-based Safe Motion Planning in Predictable Dynamic Environments
Robots have been operating in dynamic environments and shared workspaces...
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11/25/2019
A New Distribution-Free Concept for Representing, Comparing, and Propagating Uncertainty in Dynamical Systems with Kernel Probabilistic Programming
This work presents the concept of kernel mean embedding and kernel proba...
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09/18/2019
An NMPC Approach using Convex Inner Approximations for Online Motion Planning with Guaranteed Collision Freedom
Even though mobile robots have been around for decades, trajectory optim...
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02/21/2019
The BLAS API of BLASFEO: optimizing performance for small matrices
BLASFEO is a dense linear algebra library providing high-performance imp...
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11/29/2017
A Family of Iterative Gauss-Newton Shooting Methods for Nonlinear Optimal Control
This paper introduces a family of iterative algorithms for unconstrained...
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04/08/2017