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Review
. 2025 Feb 28;25(5):1519.
doi: 10.3390/s25051519.

A Survey of Robotic Monocular Pose Estimation

Kun Zhang  1 , Guozheng Song  1 , Qinglin Ai  1   2
Affiliations
Review

A Survey of Robotic Monocular Pose Estimation

Kun Zhang et al. Sensors (Basel). .

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.

Keywords: monocular SLAM; neural methods; robotic monocular pose estimation; robots; single-view OPE.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
The structure of the survey.
Figure 2
Figure 2
The pipeline of iNeRF-OPE.
Figure 3
Figure 3
An example of robotic grasping with a single object.
Figure 4
Figure 4
The distribution of coarse pose.
Figure 5
Figure 5
The tendency of neural monocular pose estimation-driven methods and semantic plugging.
See this image and copyright information in PMC

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