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Keigan ALI Support Documentation

website·Indexed 32 days ago

https://support.keigan-ali.com

Technical support and Q&A for the Keigan ALI autonomous mobile robot (AMR). Includes documentation on line tracing algorithms, self-driving positioning, obstacle sensor configuration, map data editing, Wi-Fi connectivity, and error code lists.

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What's inside Keigan ALI

  1. Overview of KeiganALI API options

    KeiganALI provides two types of APIs for system integration: REST API and MQTT API.

    • REST API (HTTP Protocol): High versatility, supports various data types including large files (e.g., images). Used for control commands and reading/writing data such as maps and task sets.
    • MQTT API (MQTT Protocol): Lightweight communication with lower CPU and power consumption. Supports bidirectional and one-to-many communication. Primarily used for retrieving AMR status (position, status, sensor information).

  2. Overview of Torque and Speed Up Modifications

    The torque and speed increase modification involves a combination of hardware replacements and software adjustments. Specifically, it requires replacing parts in the drive unit—such as the reduction gear, suspension, and bushings—and updating the software configuration settings.

  3. Overview of the ALI Optional DC-DC Converter

    The ALI Optional DC-DC Converter provides power from the 'BATT Always' port on the back of the ALI unit to three USB Type-A female ports.

    Technical Specifications:

    • Dimensions: 63 x 32 x 18 mm
    • Recommended Screw Size: M4

    Note: There are restrictions regarding I/O ports; users should refer to the official I/O port specifications documentation before installation.

  7. Understand the line tracing control algorithm

    The line tracing control algorithm operates by adjusting the robot's movement so that the center of gravity of the white mass within the 'Line Trace Mask' (ライントレースマスク) is aligned with the center of the view. Users can verify this behavior in the management tool by navigating to: Management Tool → Camera Image → Line Trace Mask.

  8. Use the Add Map Obstacles feature to define impassable areas

    The 'Add Map Obstacles' (マップ障害物の追加) feature allows users to paint black areas onto the map. These designated areas are treated as obstacles, which directly affects the system's self-position estimation and path calculation logic to ensure the robot avoids these zones.

  9. Understand KeiganALI self-localization and physical movement

    KeiganALI estimates its position on a map using LiDAR, which continuously emits lasers in a 360-degree direction up to 30 meters to measure the distance to obstacles. As long as the device is powered on and in an IDLE state (ready to drive), the system can still estimate its self-localization even if the device is physically pushed or moved by an external force.

  12. Understand the No-Go Zone (走行不可領域) functionality

    The 'No-Go Zone' (走行不可領域) is a designated area where the system will not generate paths for autonomous movement. However, even if an area is marked as a No-Go Zone, it is still utilized as a reference point for self-localization (estimating the robot's current position).