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In this work, a dynamic-Immersed--Boundary method combined with a BGK-Lattice--Boltzmann technique is developed and critically discussed. The fluid evolution is obtained on a three-dimensional lattice with 19 reticular velocities (D3Q19…

Fluid Dynamics · Physics 2022-07-14 Alessandro Coclite , Sergio Ranaldo , Giuseppe Pascazio , Marco D. de Tullio

Isolated mechanical systems -- e.g., those floating in space, in free-fall, or on a frictionless surface -- are able to achieve net rotation by cyclically changing their shape, even if they have no net angular momentum. Similarly, swimmers…

Robotic adaptation to unanticipated operating conditions is crucial to achieving persistence and robustness in complex real world settings. For a wide range of cutting-edge robotic systems, such as micro- and nano-scale robots, soft robots,…

Robotics · Computer Science 2024-04-19 Siming Deng , Noah J. Cowan , Brian A. Bittner

In this article we present the discrete-time isoholonomic problem of the planar Purcell's swimmer and solve it using the Discrete-time Pontryagin maximum principle. The 3-link Purcell's swimmer is a locomotion system moving in a low…

Systems and Control · Computer Science 2019-02-05 Sudin Kadam , Karmvir Singh Phogat , Ravi N. Banavar , Debasish Chatterjee

We study a data-driven sub-Riemannian (SR) curve optimization model for connecting local orientations in orientation lifts of images. Our model lives on the projective line bundle $\mathbb{R}^{2} \times P^{1}$, with $P^{1}=S^{1}/_{\sim}$…

Optimization and Control · Mathematics 2017-04-14 E. J. Bekkers , R. Duits , A. Mashtakov , Yu. Sachkov

We examine the optimal mass transport problem in $\mathbb{R}^{n}$ between densities having independent compact support by considering the geometry of a continuous interpolating support boundary in space-time within which the mass density…

Optimization and Control · Mathematics 2021-06-22 Anthony Yezzi

The Energy-Dissipation Principle provides a variational tool for the analysis of parabolic evolution problems: solutions are characterized as so-called null-minimizers of a global functional on entire trajectories. This variational…

Analysis of PDEs · Mathematics 2021-09-14 Luca Scarpa , Ulisse Stefanelli

This paper concerns optimal control problems for a class of sweeping processes governed by discontinuous unbounded differential inclusions that are described via normal cone mappings to controlled moving sets. Largely motivated by…

Optimization and Control · Mathematics 2018-05-01 Nguyen D. Hoang , Boris S. Mordukhovich

In deformable registration, the geometric framework - large deformation diffeomorphic metric mapping or LDDMM, in short - has inspired numerous techniques for comparing, deforming, averaging and analyzing shapes or images. Grounded in…

Artificial Intelligence · Computer Science 2022-05-11 Boulbaba Ben Amor , Sylvain Arguillère , Ling Shao

This paper reports a novel result: with proper robot models on matrix Lie groups, one can formulate the kinodynamic motion planning problem for rigid body systems as \emph{exact} polynomial optimization problems that can be relaxed as…

Robotics · Computer Science 2023-05-24 Sangli Teng , Ashkan Jasour , Ram Vasudevan , Maani Ghaffari

This article introduces a representation of dynamic meshes, adapted to some numerical simulations that require controlling the volume of objects with free boundaries, such as incompressible fluid simulation, some astrophysical simulations…

Fluid Dynamics · Physics 2022-01-26 Bruno Lévy

In this article, we present the mathematical analysis of the convergence of the linearized Crank-Nicolson Galerkin method for a nonlinear Schrodinger problem related to a domain with a moving boundary. The convergence analysis of the…

Numerical Analysis · Mathematics 2025-05-01 Daniel G. Alfaro Vigo , Daniele C. R. Gomes , Bruno A. do Carmo , Mauro A. Rincon

We determine the globally minimum time $T$ needed to translate a thin submerged flat plate a given distance parallel to its surface within a work budget. The Reynolds number for the flow is assumed to be large so that the drag on the plate…

Fluid Dynamics · Physics 2021-01-25 S. Mandre

This paper presents a gait optimization and motion planning framework for a class of locomoting systems with mixed kinematic and dynamic properties. Using Lagrangian reduction and differential geometry, we derive a general dynamic model…

Robotics · Computer Science 2025-04-29 Yanhao Yang , Ross L. Hatton

Effective locomotion in nature happens by transitioning across multiple modes (e.g., walk, run, climb). Despite this, far more mechanistic understanding of terrestrial locomotion has been on how to generate and stabilize around…

Biological Physics · Physics 2025-09-22 Ratan Othayoth , George Thoms , Chen Li

We consider the motion planning of an object in a Riemannian manifold where the object is steered from an initial point to a final point utilizing optimal control. Considering Pontryagin Minimization Principle we compute the Optimal…

Optimization and Control · Mathematics 2020-12-02 Souma Mazumdar

Lagrangian Neural Networks (LNNs) present a principled and interpretable framework for learning the system dynamics by utilizing inductive biases. While traditional dynamics models struggle with compounding errors over long horizons, LNNs…

Robotics · Computer Science 2025-06-23 Prakrut Kotecha , Aditya Shirwatkar , Shishir Kolathaya

Self-propelled colloidal swimmers move by pushing the adjacent fluid backwards. The resulting motion of an asymmetric body depends on the profile of pushing velocity over its surface. We describe a method of predicting the motion arising…

Soft Condensed Matter · Physics 2019-07-18 Thomas A. Witten , Aaron Mowitz

We consider discretized two-dimensional PDE-constrained shape optimization problems, in which shapes are represented by triangular meshes. Given the connectivity, the space of admissible vertex positions was recently identified to be a…

Optimization and Control · Mathematics 2023-08-17 Roland Herzog , Estefanía Loayza-Romero

This work explores optimization methods on hyperbolic manifolds. Building on Riemannian optimization principles, we extend the Hyperbolic Stochastic Gradient Descent (a specialization of Riemannian SGD) to a Hyperbolic Adam optimizer. While…

Machine Learning · Computer Science 2025-10-01 Yanke Wang , Kyriakos Flouris