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.
Type:
Grant
Filed:
February 16, 2023
Date of Patent:
September 19, 2023
Assignee:
ANHUI UNIVERSITY OF ENGINEERING
Inventors:
Mengyuan Chen, Pengpeng Han, Wei Wang, Tao Xu, Jinhui Liu