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Related papers: Proximal Motion Planning Algorithms

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The $s$-th higher topological complexity of a space $X$, $TC_s(X)$, can be estimated from above by homotopical methods, and from below by homological methods. We give a thorough analysis of the gap between such estimates when $X=RP^m$, the…

Algebraic Topology · Mathematics 2016-09-27 Natalia Cadavid , Jesús González , Aldo Guzmán-Sáenz

Manifolds occur naturally as configuration spaces of robotic systems. They provide global descriptions of local coordinate systems that are common tools in expressing positions of robots. The purpose of this survey is threefold. Firstly, we…

Geometric Topology · Mathematics 2024-02-13 Stephan Mescher

Although random cell complexes occur throughout the physical sciences, there does not appear to be a standard way to quantify their statistical similarities and differences. The various proposals in the literature are usually motivated by…

Computational Geometry · Computer Science 2016-06-15 Benjamin Schweinhart , Jeremy Mason , Robert MacPherson

The Topological complexity a la Farber $\text{TC}(-)$ is a homotopy invariant which have interesting applications in Robotics, specifically, in the robot motion planning problem. In this work we calculate the topological complexity of the…

Algebraic Topology · Mathematics 2019-11-12 Cesar A. Ipanaque Zapata

In this paper we study the complexity of the motion planning problem for control-affine systems. Such complexities are already defined and rather well-understood in the particular case of nonholonomic (or sub-Riemannian) systems. Our aim is…

Optimization and Control · Mathematics 2015-04-07 Frédéric Jean , Dario Prandi

By a formula of Farber the topological complexity TC(X) of a (p-1)-connected, m-dimensional CW-complex X is bounded above by (2m+1)/p+1. There are also various lower estimates for TC(X) such as the nilpotency of the ring $H^*(X\times…

Algebraic Topology · Mathematics 2012-10-24 Aleksandra Franc , Petar Pavešić

In this paper we introduce and study a new concept of parametrised topological complexity, a topological invariant motivated by the motion planning problem of robotics. In the parametrised setting, a motion planning algorithm has high…

Algebraic Topology · Mathematics 2021-09-10 Daniel C. Cohen , Michael Farber , Shmuel Weinberger

Complex networks are a powerful modeling tool, allowing the study of countless real-world systems. They have been used in very different domains such as computer science, biology, sociology, management, etc. Authors have been trying to…

Social and Information Networks · Computer Science 2014-02-04 Burcu Kantarcı , Vincent Labatut

We design a motion planning algorithm to coordinate the movements of two robots along a figure eight track, in such a way that no collisions occur. We use a topological approach to robot motion planning that relates instabilities in motion…

Robotics · Computer Science 2024-03-19 Cristian Jardon , Brian Sheppard , Veet Zaveri

The higher topological complexity of a space $X$, $\text{TC}_r(X)$, $r=2,3,\ldots$, and the topological complexity of a map $f$, $\text{TC}(f)$, have been introduced by Rudyak and Pave\v{s}i\'{c}, respectively, as natural extensions of…

Algebraic Topology · Mathematics 2023-03-24 Cesar A. Ipanaque Zapata , Jesús González

We study an elementary problem of the topological robotics: collective motion of a set of $n$ distinct particles which one has to move from an initial configuration to a final configuration, with the requirement that no collisions occur in…

Algebraic Topology · Mathematics 2007-05-23 Michael Farber , Sergey Yuzvinsky

In this paper, we deal with the robot motion planning problem in multi-valued function theory. We first enrich the multi-homotopy studies by introducing a multi-homotopy lifting property and a multi-fibration. Then we compute both a…

Algebraic Topology · Mathematics 2023-10-26 Melih İs

Motion planning is a difficult problem in robot control. The complexity of the problem is directly related to the dimension of the robot's configuration space. While in many theoretical calculations and practical applications the…

Robotics · Computer Science 2020-05-26 Felix Wiebe , Shivesh Kumar , Daniel Harnack , Malte Langosz , Hendrik Wöhrle , Frank Kirchner

We define and develop a homotopy invariant notion for the topological complexity of a map $f:X \to Y$, denoted TC($f$), that interacts with TC($X$) and TC($Y$) in the same way cat($f$) interacts with cat($X$) and cat($Y$). Furthermore,…

Algebraic Topology · Mathematics 2020-11-24 Jamie Scott

We consider the problem of approximating a two-dimensional shape contour (or curve segment) using discrete assembly systems, which allow to build geometric structures based on limited sets of node and edge types subject to edge length and…

Computational Geometry · Computer Science 2021-02-03 Andreas M. Tillmann , Leif Kobbelt

In this paper, we consider the problem of computing the nearest uncontrollable (C-uncontrollable) system to a given higher order system. The distance to the nearest uncontrollable system, also termed as the radius of controllability, is a…

Optimization and Control · Mathematics 2019-05-16 Tanay Saha , Swanand Khare , Subashish Datta

Digital topological methods are often used on computing the topological complexity of digital images. We give new results on the relation between reducibility and digital contractibility in order to determine the topological complexity of a…

General Topology · Mathematics 2022-10-05 Melih İs , İsmet Karaca

In this paper, we systematically develop the $m$-contiguity distance between simplicial maps as a discrete approximation framework for homotopical complexity in the category of simplicial complexes. We construct an increasing sequence of…

Algebraic Topology · Mathematics 2026-04-16 Nilay Ekiz Yazici , Nursultan Kuanyshov , Ayse Borat

Classification of large and dense networks based on topology is very difficult due to the computational challenges of extracting meaningful topological features from real-world networks. In this paper we present a computationally tractable…

Machine Learning · Computer Science 2022-02-04 Tananun Songdechakraiwut , Bryan M. Krause , Matthew I. Banks , Kirill V. Nourski , Barry D. Van Veen

There are many methods developed to approximate a cloud of vectors embedded in high-dimensional space by simpler objects: starting from principal points and linear manifolds to self-organizing maps, neural gas, elastic maps, various types…

Machine Learning · Statistics 2016-09-01 E. M. Mirkes , A. Zinovyev , A. N. Gorban