arXiv research

Study of motion constraints and path-following on 3D space.

High quality reconstruction with interventional C-arm cone-beam computed tomography (CBCT) requires exact geometry information. If the geometry information is corrupted, e. g., by unexpected patient or system movement, the measured signal is misplaced in the backprojection operation. With prolonged acquisition times of…

CoMPNetX uses neural networks to efficiently solve constrained motion planning problems.

New friction model for geometric locomotion systems.

We study mechanical systems subject to constraint functions that can be dependent at some points and independent at the rest. Such systems are modelled by means of generalized codistributions. We discuss how the constraint force can transmit an impulse to the motion at the points of dependence and derive an explicit fo…

Researchers created a continuous Markov martingale that mimics Brownian motion but lacks the strong Markov property.

Paper shows affine constraint is unnecessary for high-dimensional data.

Study optimal consumption with relaxed benchmarks and drawdown constraints.

Framework learns stochastic dynamics from endpoint and intermediate distributions using soft energy constraints.

Solves optimal control with state constraints using probabilistic methods.

Study optimal stopping times under regime-switching models with constraints.

Paper finds optimal selling rule for pairs trading with stock constraints.

The paper introduces a new divergence for portfolio management to outperform a benchmark.

Paper proposes incorporating road rules as a loss function for better motion planning.

This paper optimizes insurance reinsurance design under solvency constraints.

Optimal dividend payout strategy found for Brownian risk model with ratcheting constraint.

The Skorokhod embedding problem aims to represent a given probability measure on the real line as the distribution of Brownian motion stopped at a chosen stopping time. In this paper, we consider an extension of the optimal Skorokhod embedding problem to the case of finitely-many marginal constraints. Using the classic…

In this article we propose a novel geometric model to study the motion of a physical flag. In our approach a flag is viewed as an isometric immersion from the square with values in $\mathbb R^3$ satisfying certain boundary conditions at the flag pole. Under additional regularity constraints we show that the space of al…

Geodesic extensions for systems with nonholonomic constraints.

New approach approximates c-space geometry of multi-loop linkages.

The paper optimizes dividend strategies for companies with assets and liabilities under solvency constraints.

Develops integrators for nonholonomic systems on Lie groups.

New diffusion models handle constrained domains, improving generative tasks.

The paper optimizes insurance dividend payments and reinsurance strategies under specific distribution constraints.

This paper solves an optimal dividend payout problem with ratcheting constraints using a novel method.

Nonholonomic mechanical systems have been attracting more interest in recent years because of their rich geometric properties and their applications in Engineering. In all generality, we discuss the reduction of a Hamilton-Jacobi theory for systems subject to nonholonomic constraints and that are invariant under the ac…

Neural networks are increasingly used in complex (data-driven) simulations as surrogates or for accelerating the computation of classical surrogates. In many applications physical constraints, such as mass or energy conservation, must be satisfied to obtain reliable results. However, standard machine learning algorithm…

We show how the Dixon's system of first order equations of motion for the particle with inner dipole structure together with the side Mathisson constraint follows from rather general construction of the 'Hamilton system' developed by Weyssenhoff, Rund and Grässer to describe the phase space counterpart of the evolution…

New proof shows nonholonomic motions are geodesics, minimizing distance.

Study of motion control systems on Lie groups with specific geometric constraints.

Accurately predicting the possible behaviors of traffic participants is an essential capability for future autonomous vehicles. The majority of current researches fix the number of driving intentions by considering only a specific scenario. However, distinct driving environments usually contain various possible driving…

In the paper, a mean-square minimization problem under terminal wealth constraint with partial observations is studied. The problem is naturally connected to the mean-variance hedging problem under incomplete information. A new approach to solving this problem is proposed. The paper provides a solution when the underly…

In the last two decades, significant effort has been put in understanding and designing so-called structure-preserving numerical methods for the simulation of mechanical systems. Geometric integrators attempt to preserve the geometry associated to the original system as much as possible, such as the structure of the co…

Improved privacy-preserving statistical estimates with customizable noise reduction.

Study nonrigid dynamics of unitary groups on Lie groups via kinetic energy metrics.

Synthesizing human's movements such as dancing is a flourishing research field which has several applications in computer graphics. Recent studies have demonstrated the advantages of deep neural networks (DNNs) for achieving remarkable performance in motion and music tasks with little effort for feature pre-processing.…

V-SysId identifies keypoints and 3D system from unlabeled videos.

This paper considers systems subject to nonholonomic constraints which are not uniform on the whole configuration manifold. When the constraints change, the system undergoes a transition in order to comply with the new imposed conditions. Building on previous work on the Hamiltonian theory of impact, we tackle the prob…

Optimal probability measure found for constrained stochastic processes.

We study relations between vakonomically and nonholonomically constrained Lagrangian dynamics for the same set of linear constraints. The basic idea is to compare both situations at the level of variational principles, not equations of motion as has been done so far. The method seems to be quite powerful and effective.…

This paper optimizes dividend payout rates with a drawdown constraint in a stochastic model.

Constructs supermartingale couplings with full marginals constraints.

We solve the problem of optimal stopping of a Brownian motion subject to the constraint that the stopping time's distribution is a given measure consisting of finitely-many atoms. In particular, we show that this problem can be converted to a finite sequence of state-constrained optimal control problems with additional…

Given an initial (resp., terminal) probability measure $μ$ (resp., $ν$) on $\mathbb{R}^d$, we characterize those optimal stopping times $τ$ that maximize or minimize the functional $\mathbb{E} |B_0 - B_τ|^α$, $α> 0$, where $(B_t)_t$ is Brownian motion with initial law $B_0\sim μ$ and with final distribution --once stop…

This paper considers a sequence of discrete-time random walk markets with a safe and a single risky investment opportunity, and gives conditions for the existence of arbitrages or free lunches with vanishing risk, of the form of waiting to buy and selling the next period, with no shorting, and furthermore for weak conv…

In this article we consider an optimization problem of expected utility maximization of continuous-time trading in a financial market. This trading is constrained by a benchmark for a utility-based shortfall risk measure. The market consists of one asset whose price process is modeled by a Geometric Brownian motion whe…

In this work, we consider the optimal portfolio selection problem under hard constraints on trading volume amounts when the dynamics of the risky asset returns are governed by a discrete-time approximation of the Markov-modulated geometric Brownian motion. The states of Markov chain are interpreted as the states of an …

A lens cluster minimizes perimeter in the plane with given area constraints.