Fast Expanding Safe Circular Regions for Efficient Local Path Planning

Fuente: arXiv
Guardado en:
Detalles Bibliográficos
Autores principales: Fredriksson, Scott, Saradagi, Akshit, Nikolakopoulos, George
Formato: Preprint
Publicado: 2026
Materias:
Acceso en línea:
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
_version_ 1866916016166010880
author Fredriksson, Scott
Saradagi, Akshit
Nikolakopoulos, George
author_facet Fredriksson, Scott
Saradagi, Akshit
Nikolakopoulos, George
contents Local navigation is one of the fundamental problems in robot navigation, and numerous approaches have been proposed over the years, including methods such as the Dynamic Window Approach, Model Predictive Control, and more recently, Control Barrier Functions and machine learning based techniques. While these methods perform well in simple environments, many of them rely on optimization or learning based procedures that can struggle in more complex scenarios. In contrast, this article proposes a more geometric algorithmic approach that enables a local navigation method with faster computation times and longer planning horizons. The proposed method is based on the computation of a sequence of circular regions from a local LiDAR scan that expand in the direction of the goal and capture free local navigable space. The proposed method was implemented in the ROS2 framework and evaluated in a simulated environment.
format Preprint
id arxiv_https___arxiv_org_abs_2605_16009
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Fast Expanding Safe Circular Regions for Efficient Local Path Planning
Fredriksson, Scott
Saradagi, Akshit
Nikolakopoulos, George
Robotics
Local navigation is one of the fundamental problems in robot navigation, and numerous approaches have been proposed over the years, including methods such as the Dynamic Window Approach, Model Predictive Control, and more recently, Control Barrier Functions and machine learning based techniques. While these methods perform well in simple environments, many of them rely on optimization or learning based procedures that can struggle in more complex scenarios. In contrast, this article proposes a more geometric algorithmic approach that enables a local navigation method with faster computation times and longer planning horizons. The proposed method is based on the computation of a sequence of circular regions from a local LiDAR scan that expand in the direction of the goal and capture free local navigable space. The proposed method was implemented in the ROS2 framework and evaluated in a simulated environment.
title Fast Expanding Safe Circular Regions for Efficient Local Path Planning
topic Robotics
url https://arxiv.org/abs/2605.16009