Enhancing Robustness and Accuracy of 3D SLAM Algorithm Using Dempster-Shafer Theory

Abstract

Simultaneous Localization and Mapping (SLAM) is a fundamental challenge in robotics, enabling autonomous navigation for robots in unknown environments. This article explores various approaches and methods for solving SLAM in both 2D and 3D cases. This article aims to show the importance of uncertainty measurement and control and suggest possible solutions and discuss future research directions in extending algorithms like VinySLAM [1] to the 3D domain.

Keywords

• 3d slam dempster-shafer theory transferable belief model