Optimization and Path Planning of Simultaneous Localization and Mapping Construction Based on Binocular Stereo Vision

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.