A Survey of Robotic Monocular Pose Estimation

Abstract

Robotic monocular pose estimation is an important part of neural monocular pose estimation-driven methods, which includes monocular simultaneous localization and mapping (SLAM) and single-view object pose estimation (OPE) driven by neural methods. The mapping thread leeches onto robotic monocular pose estimation. Robotic monocular pose estimation consists of the localization part of monocular SLAM and the object pose solving part of single-view OPE. Depth prediction neural networks, semantics, neural implicit representations, and large language models (LLMs) are neural methods that have been important components of neural monocular pose estimation-driven methods. Complete robotic monocular pose estimation is a potential module in real robots. Possible future research directions and applications are discussed.