S&M2875 Research Paper of Special Issue
Published: March 17, 2022
Optimization and Path Planning of Simultaneous Localization and Mapping Construction Based on Binocular Stereo Vision [PDF]
Neng-Sheng Pai, Wei-Zhe Huang, Pi-Yun Chen, and Shih-An Chen
(Received June 19, 2021; Accepted August 23, 2021)
Keywords: simultaneous localization and mapping (SLAM), random sample consensus (RANSAC), D*Lite, closed-loop detection
The aim of this study is to help individuals easily reach their destinations independently whenever they are situated in an unfamiliar environment. After performing pre-processing optimization, a map constructed by simultaneous localization and mapping (SLAM) is inputted to a route planning algorithm to find the most suitable path. The proposed method utilizes a stereo camera sensor to take images of the environment, after which it conducts 2D/3D mapping through the SLAM framework before converting the constructed map into images. Then, obstacles are identified using an image segmentation method, and pseudo-obstacles are filtered out through optimization. Finally, route planning is conducted using the D*Lite algorithm. Experimental results revealed that most of the pseudo-obstacles can be filtered out through image optimization, thereby increasing the accuracy of the 2D map.Corresponding author: Neng-Sheng Pai
This work is licensed under a Creative Commons Attribution 4.0 International License.
Cite this article
Neng-Sheng Pai, Wei-Zhe Huang, Pi-Yun Chen, and Shih-An Chen, Optimization and Path Planning of Simultaneous Localization and Mapping Construction Based on Binocular Stereo Vision, Sens. Mater., Vol. 34, No. 3, 2022, p. 1091-1104.