Application of Slam Method in Big Data Rural Tourism Management in Dynamic Scene

preprint OA: closed CC-BY-4.0
📄 Open PDF View at publisher

Abstract

Under the background of the rapid development of science and technology, technologies in many fields are advancing accordingly. The same artificial intelligence and computer vision technologies are also constantly being updated. Similarly, in vision On the basis of, positioning and mapping (technology is the core technology for mobile robots to complete the intelligentization) has also had a great response in the academic and industrial circles, and has attracted the attention of most scholars. Today, the construction of smart tourism is in a prosperous stage. Based on the big data of rural tourism construction in a certain province, this article mainly uses the SLAM method that relies on visual characteristics under dynamic scenes to study the construction of rural tourism platform. In this paper, considering the influence of many factors, based on the ORB-SLAM2 system, a visual SLAM system is established. At the same time, the mathematical model of the SLAM system is established and used RGB-D The depth camera is used as the input sensor, the visual odometer locates the camera, the nonlinear optimization optimizes the data association, the closed-loop detection completes the camera repositioning, the map construction completes the environment description and other multi-module collaborations, which together complete the simultaneous positioning of the camera and the map Build work.

My notes (saved in your browser only)

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.

Source provenance

europepmc
last seen: 2026-05-19T01:45:01.086888+00:00
unpaywall
last seen: 2026-05-26T02:00:01.498150+00:00
License: CC-BY-4.0