A robot-driven method for cleaning up coal deposits, and electronic equipment.

By using a robot-driven method to clean up coal accumulation, multimodal data acquisition and BIM modeling are employed to locate the coal accumulation space, identify the state of coal dust, and optimize the cleaning trajectory. This method achieves efficient and safe coal bunker cleaning, solving the problems of low efficiency and safety hazards in existing technologies.

CN121535755BActive Publication Date: 2026-05-26BEIJING HUADIAN TIANREN ELECTRIC POWER CONTROL TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
BEIJING HUADIAN TIANREN ELECTRIC POWER CONTROL TECH
Filing Date
2026-01-16
Publication Date
2026-05-26

AI Technical Summary

Technical Problem

Existing technologies for cleaning up coal deposits are inefficient, labor-intensive, environmentally unfriendly, and pose safety hazards. They are also incomplete and inefficient.

Method used

A robot-driven method for cleaning up coal accumulation was adopted. A multimodal millimeter-level point cloud model was constructed by panoramic multimodal data acquisition. The spatial coordinates of the coal accumulation were located by combining the BIM benchmark model, the state of coal dust was identified, the cleaning sub-tasks were aggregated and the spatiotemporal trajectory was optimized, and the collaborative operation of the robot and the robotic arm was realized.

Benefits of technology

It improves the efficiency of coal accumulation cleaning, ensures safety and cleaning effect, reduces labor intensity, and solves the problems of incomplete cleaning and insufficient efficiency in existing technologies.

✦ Generated by Eureka AI based on patent content.

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Abstract

This invention discloses a robot-driven method and electronic device for cleaning accumulated coal, relating to the field of coal cleaning technology. The method includes: constructing a multimodal millimeter-level point cloud model; locating the spatial coordinates of distributed coal to be cleaned; extracting distributed composite physical features from the multimodal millimeter-level point cloud model to identify the state of coal powder, and outputting distributed coal powder physical state data; aggregating the distributed coal powder physical state data to obtain multiple sets of coal cleaning sub-tasks; optimizing the spatiotemporal coupling of the multiple sets of coal cleaning sub-tasks based on the spatial coordinates of the distributed coal to be cleaned, and outputting a collaborative coal cleaning trajectory; and simultaneously controlling the robotic arm to perform global coal cleaning of the coal bunker according to a multi-degree-of-freedom joint spatial trajectory while driving the coal cleaning robot to move along the displacement trajectory of the mobile robot base. This solves the technical problem of low coal cleaning efficiency in existing technologies and achieves the technical effect of improving coal cleaning efficiency.
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