Multi-sensor nonlinear tightly-coupled composite robot positioning mapping system

Through a multi-sensor nonlinear tight coupling system, combined with lidar, VIO module and inertial navigation unit, the fusion of RGB vision sensors and infrared vision sensors is solved, and the positioning accuracy and reliability of composite robots under light changes and other interferences is achieved, achieving high-precision positioning under different environmental conditions.

CN120043519APending Publication Date: 2025-05-27JIN HOUNG FUH (CHUZHOU) CONVEYING EQUIP CO LTD +1
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Patent Information

Application Number
CN202510200693.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-02-24
Publication Date
2025-05-27

AI Technical Summary

Technical Problem

Composite robots are difficult to achieve high-precision and reliable environmental perception and their own posture measurement under problems such as light changes, external interference, reflected surface influence and accumulated errors.

Method used

A multi-sensor nonlinear tight coupling system is adopted, combined with sensors such as lidar, VIO module, inertial navigation unit, etc., through the fusion of RGB vision sensors and infrared vision sensors, the fusion of illuminance value calculation model and inertial navigation is achieved to realize real-time calculation and correction of positioning information.

Benefits of technology

It improves the positioning accuracy and reliability of composite robots under different environmental conditions, reduces the impact of light changes and other interference on the positioning system, and ensures accurate positioning estimation under different illuminances.

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Abstract

The invention discloses a multi-sensor nonlinear tight coupling composite robot positioning and mapping system, and relates to the technical field of measurement, RGB frame data is collected through an RGB visual sensor unit, infrared frame data is collected through an infrared visual sensor unit, the collected RGB frame data and infrared frame data are input into an illumination value calculation model unit for calculation, and the illumination value calculation model unit is used for calculating the illumination value. Effective tight coupling data of the infrared frame and the RGB frame is fused with I MU data, according to the characteristic that the I MU is fast in instantaneous response, a measured value of the I MU data is used for driving a process model to adapt to the maneuverability of the robot, and according to the characteristic that accumulated errors cannot be generated in stereoscopic vision, the maneuverability of the robot is improved. The positioning estimation result of stereoscopic vision is used as the observation value of the observation model to correct the error of I MU data, and the use right ratio of the infrared vision sensor unit and the RGB vision sensor unit is calculated and controlled through the vision inertial navigation fusion unit to ensure that the accurate positioning estimation result can be obtained under different illuminance.
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Citation Information

Patent Citations

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