Robot gesture frame selection tracking control system and method based on wearable vision

By introducing wearable visual equipment and gesture recognition technology into the mobile robot control system, the problem of low target selection and tracking efficiency in the prior art is solved, and more efficient and accurate target tracking control is achieved.

CN119704147APending Publication Date: 2025-03-28QILU UNIVERSITY OF TECHNOLOGY (SHANDONG ACADEMY OF SCIENCES)
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Patent Information

Application Number
CN202411811249.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-10
Publication Date
2025-03-28

AI Technical Summary

Technical Problem

The existing mobile robot control method based on wearable devices cannot quickly and effectively select and track targets in surveillance videos, limiting operational efficiency and accuracy.

Method used

A robot gesture box selection tracking control system based on wearable vision is adopted to obtain operator gesture images through wearable cameras, and a gesture category is identified using feature detection and gesture classification algorithms, and the tracking control strategy of the mobile robot is determined based on the gesture category.

Benefits of technology

It realizes that the operator quickly and accurately selects the target to be tracked in the surveillance video, and improves the accuracy and response speed of target tracking, enhancing the robot's adaptability and collaboration capabilities in complex environments.

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Abstract

The invention discloses a robot gesture frame selection tracking control method and system based on wearable vision, and belongs to the technical field of mobile robot control. Comprises: obtaining an operator gesture image; processing the gesture image of the operator through a feature detection algorithm, and extracting a plurality of feature points; the feature points are classified and recognized through a gesture classification algorithm, and gesture categories are determined; and determining a tracking control strategy of the controlled end mobile robot by taking the gesture category as a selection basis of a target tracking area and a triggering condition of a tracking instruction, and sending the tracking control strategy to the controlled end mobile robot. The target tracking accuracy, the response speed and the task execution efficiency are improved, and the problem that the application efficiency of the mobile robot in actual operation is limited due to the fact that the existing target selection process does not reach enough accuracy is solved.
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