Fast Expanding Safe Circular Regions for Efficient Local Path Planning

2026-05-15

AI Summary

This work proposes a geometry-based local navigation algorithm to address the limitations of existing local path planning methods, which often suffer from low computational efficiency and short planning horizons in complex environments. The proposed approach directly constructs a sequence of safe circular regions extending toward the goal from raw local LiDAR scans, efficiently characterizing traversable space without relying on optimization or learning-based components. By leveraging purely geometric constructions, the method significantly enhances computational speed and extends the effective planning horizon. Implemented using LiDAR data and integrated within the ROS 2 framework, the algorithm demonstrates clear advantages over conventional approaches in terms of both computational efficiency and achievable planning distance, as validated in simulated environments.

Abstract

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.

Problem

• local path planning
• robot navigation
• computational efficiency
• planning horizon
• complex environments

Innovation

• geometric algorithm
• safe circular regions
• local path planning
• LiDAR-based navigation
• ROS2