Reinforcement learning-based label-free six-dimensional object pose prediction method and apparatus
US12430798B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 5, 2022 |
| Grant date | Sep 30, 2025 |
| Priority date | — |
| Expiry date | May 16, 2044 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02T10/40
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Provided are a reinforcement learning-based label-free six-dimensional object pose prediction method and apparatus. The method includes: obtaining a target image to be predicted, the target image being a two-dimensional image including a target object; performing pose prediction based on the target image by using a pre-trained pose prediction model to obtain a prediction result, the pose prediction model being obtained by performing reinforcement learning based on a sample image; and determining a three-dimensional position and a three-dimensional direction of the target object based on the prediction result. The pose prediction model is trained by introducing reinforcement learning, the pose prediction is performed based on the target image by using the pre-trained pose prediction model, and thus the problem of six-dimensional object pose estimation based on two-dimensional images can be solved in the absence of real pose annotation, which ensures the prediction effect of label-free six-dimensional object pose prediction.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.