Time-of-Flight LiDAR-based Precise Mapping

TL;DR

This paper presents a probabilistic map update method for LiDAR-based robotic mapping that estimates the number of exploration rounds needed, addressing noise and accuracy issues in map creation.

Contribution

It introduces a novel probabilistic approach for map updating in LiDAR-based mapping, with a focus on estimating exploration rounds to optimize hardware and time resources.

Findings

The method effectively estimates the required exploration rounds.

It improves map accuracy by accounting for sensor noise.

The approach reduces hardware and time costs in robotic mapping.

Abstract

Last two decades, the problem of robotic mapping has made a lot of progress in the research community. However, since the data provided by the sensor still contains noise, how to obtain an accurate map is still an open problem. In this note, we analyze the problem from the perspective of mathematical analysis and propose a probabilistic map update method based on multiple explorations. The proposed method can help us estimate the number of rounds of robot exploration, which is meaningful for the hardware and time costs of the task.