Correspondence-Free Relative Pose Estimation: A Global Approach With Sparse Feature-Guided Directional Embedding
Estimating the six degrees of freedom relative poses is a fundamental problem in robotics. Generally, correspondence-based methods are often vulnerable to mismatches in features between the source and the target. This paper presents an alternative approach: estimating the relative pose globally with