Three-dimensional Reconstruction of Grassland Landforms Based on Intelligent Robot Vision System and Numerical Simulation of Its Characteristics

Abstract

Grassland is an important component in the natural ecosystem. Geological detection and numerical analysis of grassland landforms are the main ways to protect and develop grassland ecological environment. However, the traditional grassland geological survey is not effective. The displayed grassland landforms are not intuitive and the numerical fitting accuracy is low, seriously affecting the work efficiency of grassland landform survey. With the development of machine vision, cloud computing and other technologies, the intelligent robot vision system has stable spatial positioning and construction capabilities. Using the intelligent robot vision system, the grassland landform was reconstructed in 3D (three-dimension) and compared with the traditional grassland landform construction. The experimental results showed that the accuracy of the 3D modeling based on the intelligent robot vision system and the traditional 3D reconstruction in the 6th test of the square grassland with a side of 2km was 96% and 72% respectively. In a square grassland area with a side length of 2km, the average matching degrees of the two 3D modeling feature data were 89.3% and 73.3% respectively. Therefore, the intelligent robot vision system can improve the accuracy of 3D reconstruction of grassland and the accuracy of feature numerical simulation.