Mowing robot pose updating method

By combining sensors such as LiDAR, cameras, inertial measurement units, and wheel speedometers, along with filtering fusion and coordinate transformation using absolute attitude sensors, the problems of attitude dependence and error accumulation in the pose update of lawnmower robots have been solved, improving positioning and navigation accuracy and enhancing ground cover efficiency.

CN122306057APending Publication Date: 2026-06-30GUANGDONG XINBAO ELECTRICAL APPLIANCES HLDG CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
GUANGDONG XINBAO ELECTRICAL APPLIANCES HLDG CO LTD
Filing Date
2026-04-10
Publication Date
2026-06-30

AI Technical Summary

Technical Problem

Existing pose update methods for lawnmower robots rely on sensors such as cameras and lidar, resulting in a high degree of attitude dependence and large cumulative errors over long distances, failing to effectively solve the problems of high attitude dependence and error accumulation.

Method used

By employing sensors such as lidar, cameras, inertial measurement units, and wheel speedometers, combined with an absolute attitude sensor, and through filtering fusion and coordinate transformation, the local pose and global pose are aligned and updated, eliminating cumulative pose errors.

Benefits of technology

It improves the positioning and navigation accuracy of lawn mowing robots in grassland management and agricultural fields, reduces attitude dependence, and improves ground cover efficiency.

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Abstract

This application provides a method for updating the pose of a lawnmower robot, including obtaining the robot's local pose at the current moment based on sensors; aligning the local pose with the global pose of an absolute attitude sensor; determining the mowing path of the entire map and identifying and collecting boundary points based on the aligned global pose; and performing transformation processing on the coordinates of the boundary points to update the robot's global pose. By fusing multiple sources of sensors such as LiDAR and cameras through an absolute attitude sensor, the method eliminates problems such as cumulative pose errors and high pose dependence generated by the lawnmower robot during movement, thereby improving the robot's coverage efficiency.
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