PAINT REPAIR PROCESS BY SCENARIO
    1.
    发明申请

    公开(公告)号:US20220126319A1

    公开(公告)日:2022-04-28

    申请号:US17425035

    申请日:2019-08-23

    Abstract: A method and associated system provides automated abrasive paint repair using automated abrasive paint repair devices that selectively sand, buff, and polish a substrate in response to received instructions generated by a controller. The controller receives coordinates of each identified defect in the substrate along with parameters describing characteristics of each defect, selects a sanding process, a buffing process, and/or a polishing process based on empirically derived rules established by skilled/expert human operators and the received parameters. The controller outputs instructions to cause the automated abrasive paint repair devices to execute the selected sanding process, buffing process, and/or polishing process using the received parameters. The empirically derived rules and parameters may be stored in a lookup table and/or updated by a machine learning module.

    Paint repair process by scenario
    3.
    发明授权

    公开(公告)号:US12275038B2

    公开(公告)日:2025-04-15

    申请号:US17425035

    申请日:2019-08-23

    Abstract: A method and associated system provides automated abrasive paint repair using automated abrasive paint repair devices that selectively sand, buff, and polish a substrate in response to received instructions generated by a controller. The controller receives coordinates of each identified defect in the substrate along with parameters describing characteristics of each defect, selects a sanding process, a buffing process, and/or a polishing process based on empirically derived rules established by skilled/expert human operators and the received parameters. The controller outputs instructions to cause the automated abrasive paint repair devices to execute the selected sanding process, buffing process, and/or polishing process using the received parameters. The empirically derived rules and parameters may be stored in a lookup table and/or updated by a machine learning module.

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