LiDAR-based SLAM for robotic mapping: state of the art and new frontiers

TL;DR

This paper reviews the current state of LiDAR-based SLAM techniques for robotic mapping, compares various algorithms, and discusses future challenges and emerging frontiers in the field.

Contribution

It provides a comprehensive survey focusing on different LiDAR types and configurations, including comparative analysis and insights into future research directions.

Findings

LiDAR configurations significantly impact SLAM performance

Comparative analysis highlights strengths and weaknesses of algorithms

Emerging frontiers include multi-sensor integration and real-time processing

Abstract

In recent decades, the field of robotic mapping has witnessed widespread research and development in LiDAR (Light Detection And Ranging)-based simultaneous localization and mapping (SLAM) techniques. In this paper, we review the state-of-the-art in LiDAR-based SLAM and explore the remaining challenges that still require attention to satisfy the needs of contemporary applications. A distinctive aspect of this study lies in its literature survey, which specifically investigates the application of various types and configurations of LiDAR, setting it apart from prior reviews. Furthermore, several representative comparisons of LiDAR-based SLAM algorithms are presented, which can serve as a point of reference. Finally, the paper concludes with an insightful discussion on the emergence of new frontiers in the domain of LiDAR-based SLAM.