Deep learning based robot target recognition and motion detection method, storage medium and apparatus
US11763485B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 16, 2023 |
| Grant date | Sep 19, 2023 |
| Priority date | — |
| Expiry date | Feb 16, 2043 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02T10/40
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present invention discloses deep learning based robot target recognition and motion detection methods, storage media and devices, the method consists of the following steps: Step S1. adding masks to regions where potentially dynamic objects are located through instance segmentation networks incorporating attention mechanisms and positional coding; Step S2, estimation of the camera pose using static feature points outside the instance segmentation mask in the scene; Step S3, estimation of the object pose transformation matrix from the camera pose; Step S4, determining the state of motion of the object's characteristic points from the relationship between motion parallax and differential entropy, and thus the state of motion of the object as a whole; Step S5, rejects the dynamic objects therein and repairs the static background of the rejected area for positional estimation and map construction. The invention improves the accuracy of segmented boundaries of occluded dynamic objects, and the rejection of dynamic region feature points reduces the impact of dynamic objects on the system.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.