Research on Multi-Sensor Data Collection and Mapping Methods

Abstract

In today's information society, the importance of collecting data through multiple channels continues to increase. This article focuses on the use of drones for large-area forest information collection and tree analysis. In complex environments, there are a series of problems in obtaining tree mapping information with a single sensor, such as single use scenarios, low accuracy, limited viewing angles, and high requirements for computing power. To address these challenges, this paper proposes a Bayesian-based multi-sensor fusion strategy to overcome the limitations of a single sensor by integrating depth camera and lidar data. Experimental results show that the proposed method significantly improves the accuracy of mapping surrounding trees and the ability to collect information. The multi-sensor fusion strategy effectively reduces the problem of repeated data processing and improves the comprehensiveness of collected data. It meets the requirements of real-time performance and accurate collection of surrounding scenes.