Object Dimension Extraction for Environment Mapping with Low Cost Cameras Fused with Laser Ranging

TL;DR

This paper presents a low-cost environment mapping method that fuses laser ranging with stereo camera data to accurately extract object dimensions in unknown terrains, aiding applications like exploration and disaster relief.

Contribution

It introduces a novel fusion approach combining laser ranging and stereo vision with a new disparity noise reduction technique for environment mapping.

Findings

Effective object dimension extraction in unknown terrains

Reduced disparity noise improves mapping accuracy

Fusion of laser and stereo data enhances environment understanding

Abstract

It is essential to have a method to map an unknown terrain for various applications. For places where human access is not possible, a method should be proposed to identify the environment. Exploration, disaster relief, transportation and many other purposes would be convenient if a map of the environment is available. Replicating the human vision system using stereo cameras would be an optimum solution. In this work, we have used laser ranging based technique fused with stereo cameras to extract dimension of objects for mapping. The distortions were calibrated using mathematical model of the camera. By means of Semi Global Block Matching [1] disparity map was generated and reduces the noise using novel noise reduction method of disparity map by dilation. The Data from the Laser Range Finder (LRF) and noise reduced vision data has been used to identify the object parameters.