TDLE: 2-D LiDAR Exploration With Hierarchical Planning Using Regional Division

TL;DR

This paper introduces TDLE, a hierarchical planning framework for 2D LiDAR exploration that efficiently generates global routes by dividing the space into subregions, improving exploration efficiency with minimal resources.

Contribution

The work presents a novel hierarchical planning approach that dynamically partitions the exploration space and guides exploration using subregion indicators, reducing computational costs.

Findings

Outperforms existing 2D LiDAR exploration methods in simulations

Demonstrates effectiveness in real-world field tests

Reduces computational resources needed for global planning

Abstract

Exploration systems are critical for enhancing the autonomy of robots. Due to the unpredictability of the future planning space, existing methods either adopt an inefficient greedy strategy or require a lot of resources to obtain a global solution. In this work, we address the challenge of obtaining global exploration routes with minimal computing resources. A hierarchical planning framework dynamically divides the planning space into subregions and arranges their orders to provide global guidance for exploration. Indicators that are compatible with the subregion order are used to choose specific exploration targets, thereby considering estimates of spatial structure and extending the planning space to unknown regions. Extensive simulations and field tests demonstrate the efficacy of our method in comparison to existing 2D LiDAR-based approaches. Our code has been made public for further investigation.