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$\ell_0$ constrained optimization is prevalent in machine learning, particularly for high-dimensional problems, because it is a fundamental approach to achieve sparse learning. Hard-thresholding gradient descent is a dominant technique to…

Machine Learning · Computer Science 2024-03-19 William de Vazelhes , Hualin Zhang , Huimin Wu , Xiao-Tong Yuan , Bin Gu

Starting from the Hamiltonian representation of the dynamics in \cite{rosengren2015chaos,colombo2019long}, this work proposes an innovative procedure to design fully-analytical maneuvers for post-mission disposal of HEOs satellites,…

Earth and Planetary Astrophysics · Physics 2024-01-29 Francesca Scala , Ioannis Gkolias , Camilla Colombo

We present a robotics-oriented, coordinate-free formulation of inverse flight dynamics for fixed-wing aircraft on SO(3). Translational force balance is written in the world frame and rotational dynamics in the body frame; aerodynamic…

Robotics · Computer Science 2026-04-30 Antonio Franchi , Chiara Gabellieri

This paper presents a computationally efficient optimization algorithm for solving nonconvex optimal control problems that involve discrete logic constraints. Traditional solution methods for these constraints require binary variables and…

Optimization and Control · Mathematics 2021-07-16 Danylo Malyuta , Behcet Acikmese

In this work, we aim at efficiently solving a parametrized family of optimal transport problems by using model order reduction methods. We propose a reduced-order model by adding to the primal (respectively dual) version of the…

Numerical Analysis · Mathematics 2026-04-13 Elise Bonnet-Weill , Virginie Ehrlacher , Luca Nenna

Future multi-spacecraft missions require robust autonomous trajectory optimization capabilities to ensure safe and efficient rendezvous operations. This capability hinges on solving non-convex optimal control problems in real-time, although…

Optimization and Control · Mathematics 2025-01-28 Yuji Takubo , Tommaso Guffanti , Daniele Gammelli , Marco Pavone , Simone D'Amico

We propose enhancing trajectory optimization methods through the incorporation of two key ideas: variable-grasp pose sampling and trajectory commitment. Our iterative approach samples multiple grasp poses, increasing the likelihood of…

Robotics · Computer Science 2023-05-23 Jiahe Pan , Kerry He , Jia Ming Ong , Akansel Cosgun

We present a framework for bi-level trajectory optimization in which a system's dynamics are encoded as the solution to a constrained optimization problem and smooth gradients of this lower-level problem are passed to an upper-level…

Preliminary spacecraft trajectory optimization is a parameter dependent global search problem that aims to provide a set of solutions that are of high quality and diverse. In the case of numerical solution, it is dependent on the original…

Optimization and Control · Mathematics 2024-12-31 Ryne Beeson , Anjian Li , Amlan Sinha

A minimum-time reorientation of an axisymmetric rigid spacecraft controlled by three torques is studied. The orientation of the body is modeled such that the attitude kinematics are representative of a spin-stabilized spacecraft. The…

Optimization and Control · Mathematics 2022-03-23 Elisha R. Pager , Anil V. Rao

Automatically generating agile whole-body motions for legged and humanoid robots remains a fundamental challenge in robotics. While numerous trajectory optimization approaches have been proposed, there is no clear guideline on how the…

Robotics · Computer Science 2025-08-18 Evangelos Tsiatsianas , Chairi Kiourt , Konstantinos Chatzilygeroudis

In this paper, we present a bi-level optimal control framework for designing low-thrust spacecraft trajectories with robustness against missed-thrust-events. The upper-level (UL) problem generates a nominal trajectory assuming full control…

Optimization and Control · Mathematics 2025-12-23 Amlan Sinha , Ryne Beeson

Fine-tuning Large Language Models (LLMs) has proven effective for a variety of downstream tasks. However, as LLMs grow in size, the memory demands for backpropagation become increasingly prohibitive. Zeroth-order (ZO) optimization methods…

Machine Learning · Computer Science 2025-07-25 Ziming Yu , Pan Zhou , Sike Wang , Jia Li , Mi Tian , Hua Huang

This paper presents a novel Lagrangian approach to attitude tracking for rigid spacecraft using unit quaternions, where the motion equations of a spacecraft are described by a four degrees of freedom Lagrangian dynamics subject to a…

Systems and Control · Electrical Eng. & Systems 2022-02-11 Eduardo Espíndola , Yu Tang

The present work considers the optimal control of a convective Cahn-Hilliard system, where the control enters through the velocity in the transport term. We prove the existence of a solution to the considered optimal control problem. For an…

Optimization and Control · Mathematics 2018-03-08 Carmen Gräßle , Michael Hinze , Nicolas Scharmacher

Zero-order optimization techniques are becoming increasingly popular in robotics due to their ability to handle non-differentiable functions and escape local minima. These advantages make them particularly useful for trajectory optimization…

Robotics · Computer Science 2025-10-13 Armand Jordana , Jianghan Zhang , Joseph Amigo , Ludovic Righetti

Space robotics applications, such as Active Space Debris Removal (ASDR), require representative testing before launch. A commonly used approach to emulate the microgravity environment in space is air-bearing based platforms on flat-floors,…

Autonomous terrain traversal of articulated tracked robots can reduce operator cognitive load to enhance task efficiency and facilitate extensive deployment. We present a novel hybrid trajectory optimization method aimed at generating…

Robotics · Computer Science 2023-11-27 Zhengzhe Xu , Yanbo Chen , Zhuozhu Jian , Junbo Tan , Xueqian Wang , Bin Liang

This report is an introduction to transcription methods for trajectory optimization techniques. The first few sections describe the two classes of transcription methods (shooting \& simultaneous) that are used to convert the trajectory…

Optimization and Control · Mathematics 2017-07-04 Matthew P. Kelly

High-order implicit shock tracking (fitting) is a class of high-order, optimization-based numerical methods to approximate solutions of conservation laws with non-smooth features by aligning elements of the computational mesh with…

Numerical Analysis · Mathematics 2024-01-30 Charles J. Naudet , Matthew J. Zahr