arXiv research

Geodesics in 3D space with 1-2 analytic obstacles, proving geodesic independence.

New boundary condition for weak inverse mean curvature flow in bounded domains.

Method recovers obstacles from travel times on curved surfaces.

Paper tackles utility maximization with job-switching and retirement constraints.

Study finds a limiting distribution for free path lengths on flat surfaces with circular obstacles.

In this paper, we show the existence of real-analytic stationary Navier-Stokes flows with isotropic streamlines in all latitudes in some simply-connected flow region on a rotating round sphere. We also exclude the possibility of having a Poiseuille's flow profile to be one of these stationary Navier-Stokes flows with i…

Study on elastic curves pinned at the boundary, focusing on minimizers and their interaction with obstacles.

Study of mean curvature flow with obstacles using singular perturbation.

The paper deals with some problems related to recovering information about an obstacle in an Euclidean space from certain measurements of lengths of generalized geodesics in the exterior of the obstacle. The main result is that if two obstacles satisfy some generic regularity conditions and have (almost) the same trave…

New approach for obstacle avoidance in robotics using learned representations.

The paper finds local minimizers for obstacle avoidance on curved spaces.

Same travelling times imply identical obstacles in Riemannian manifolds.

The paper simplifies conditions for optimal paths on manifolds avoiding obstacles.

Study anisotropic obstacle problem for minimal surfaces using Cahn-Hoffman transform.

Study proves uniqueness for ray transform on surfaces with obstacles.

We consider the broken ray transform on Riemann surfaces in the presence of an obstacle, following earlier work of Mukhometov. If the surface has nonpositive curvature and the obstacle is strictly convex, we show that a function is determined by its integrals over broken geodesic rays that reflect on the boundary of th…

Anisotropic obstacle problems and Stefan problem studied with evolving surfaces.

Geometric optics describes wave behavior near convex obstacles.

We consider an obstacle problem for elastic curves with fixed ends. We attempt to extend the graph approach provided in [8]. More precisely, we investigate nonexistence of graph solutions for special obstacles and extend the class of admissible curves in a way that an existence result can be obtained by a penalization …

We show short time existence and uniqueness of $\C^{1,1}$ solutions to the mean curvature flow with obstacles, when the obstacles are of class $\C^{1,1}$. If the initial interface is a periodic graph we show long time existence of the evolution and convergence to a minimal constrained hypersurface.

Analyzes symmetries in neural networks to predict learning dynamics.

In this paper, we analyze a real-valued reflected backward stochastic differential equation (RBSDE) with an unbounded obstacle and an unbounded terminal condition when its generator $f$ has quadratic growth in the $z$-variable. In particular, we obtain existence, comparison, and stability results, and consider the opti…

This paper presents preliminary work on learning the search heuristic for the optimal motion planning for automated driving in urban traffic. Previous work considered search-based optimal motion planning framework (SBOMP) that utilized numerical or model-based heuristics that did not consider dynamic obstacles. Optimal…

Motivated by analogies with basic density theorems in analytic number theory, we introduce a notion (and variations) of the homological density of one space in another. We use Weil's number field/ function field analogy to predict coincidences for limiting homological densities of various sequences $\mathcal{Z}^{(d_1,\…

Billiard trajectories in curved spaces have predictable travel times.

In this paper we study Backward Stochastic Differential Equations with two reflecting right continuous with left limits obstacles (or barriers) when the noise is given by Brownian motion and a Poisson random measure mutually independent. The jumps of the obstacle processes could be either predictable or inaccessible. W…

New DAG constraints improve differentiable DAG learning.

Many mobile robots rely on 2D laser scanners for localization, mapping, and navigation. However, those sensors are unable to correctly provide distance to obstacles such as glass panels and tables whose actual occupancy is invisible at the height the sensor is measuring. In this work, instead of estimating the distance…

Billiard trajectories (broken generalised geodesics) are considered in the exterior of an obstacle $K$ with smooth boundary on an arbitrary Riemannian manifold. We prove a generalisation of the well-known Santalo's formula. As a consequence, it is established that if the set of trapped points has positive measure, then…

We consider the problem of evolving hypersurfaces by mean curvature flow in the presence of obstacles, that is domains which the flow is not allowed to enter. In this paper, we treat the case of complete graphs and explain how the approach of M. Saez and the second author yields a global weak solution to the original p…

A framework for navigating environments with spatially correlated obstacles and uncertain blockage status.

GP-ND avoids obstacles in trajectory planning using Gaussian Process regression.

Flow adjusts curvature to avoid a fixed region, proving bounds and regularity.

Study motion planning for points avoiding obstacles in a plane.

The Heston stochastic volatility process is a degenerate diffusion process where the degeneracy in the diffusion coefficient is proportional to the square root of the distance to the boundary of the half-plane. The generator of this process with killing, called the elliptic Heston operator, is a second-order, degenerat…

We prove that if two non-trapping obstacles in $\mathbb{R}^n$ satisfy some rather weak non-degeneracy conditions and the scattering rays in their exteriors have (almost) the same travelling times or (almost) the same scattering length spectrum, then they coincide.

Paper studies optimal control for a specific geometric problem.

Study on semiconcavity of solutions to gradient obstacle problems on compact manifolds.

We develop some of the basic theory for the obstacle problem on Riemannian Manifolds, and we use it to establish a mean value theorem. Our mean value theorem works for a very wide class of Riemannian manifolds and has no weights at all within the integral.

Coordinated defensive escorts can aid a navigating payload by positioning themselves in order to maintain the safety of the payload from obstacles. In this paper, we present a novel, end-to-end solution for coordinating an escort team for protecting high-value payloads. Our solution employs deep reinforcement learning …

Rigidity of travel times for convex obstacles in Riemannian manifolds is proven.

By introducing a shape manifold as a solution set to solve inverse obstacle scattering problems we allow the reconstruction of general, not necessarily star-shaped curves. The bending energy is used as a stabilizing term in Tikhonov regularization to gain independence of the parametrization. Moreover, we discuss how se…

The paper studies the properties of maps with free boundaries, focusing on the obstacle case.

Investigates polar tangential angles of curves and their monotonicity.

Optimal controls for conformal Laplacian obstacle problems on spheres and manifolds.

Improved covariance matrix estimation for portfolio optimization with guaranteed PSD and controlled conditioning.

We study periodic wind-tree models, billiards in the plane endowed with $\mathbb{Z}^2$-periodically located identical connected symmetric right-angled obstacles. We show asymptotic formulas for the number of (isotopy classes of) closed billiard trajectories (up to $\mathbb{Z}^2$-translations) on the wind-tree billiard.…

Deep network learns Obstacle Tower challenge without human demonstrations.