Multi-source information fusion robot positioning method and system for unstructured environment

Through a multi-source information fusion method, combined with laser point cloud, images and acceleration data, the problem of fluctuations in positioning accuracy of mobile robots in unstructured environments is solved, achieving highly robust real-time positioning and stable operation under harsh conditions.

CN114689037AActive Publication Date: 2022-07-01SHANDONG YOUBAOTE INTELLIGENT ROBOTICS CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SHANDONG YOUBAOTE INTELLIGENT ROBOTICS CO LTD
Filing Date
2022-03-31
Publication Date
2022-07-01

AI Technical Summary

⚠Technical Problem

Mobile robots that acquire accurate pose information in real-time in unstructured environments face challenges caused by factors such as lighting changes, rain and snow, and geometric structure degradation. Existing single-sensor positioning methods fluctuate or fail in positioning accuracy under harsh conditions.

⚗Method used

Using a multi-source information fusion method, combined with real-time laser point cloud, image information and acceleration data, through point cloud registration, visual relocation and inertial measurement, an optimized objective function is constructed for iterative calculation, and the Gaussian distribution of the prediction and measurement model is used to perform state Prediction and update to achieve filtering and fusion of robot positioning information.

🎯Benefits of technology

It improves the anti-interference ability in dynamic and complex environments, has strong adaptability and high stability, and can achieve highly robust real-time positioning in severe weather and geometrically degraded areas, ensuring the stable operation of the robot in the operating environment.

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Abstract

According to the multi-source information fusion robot positioning method and system for the unstructured environment provided by the invention, fusion processing is carried out on multi-source information data such as laser point cloud, environment image information and acceleration which are acquired in real time, so that the multi-source information fusion robot positioning method and system for the unstructured environment can be realized in a severe weather state and a dynamic unstructured environment. Carrying out high-robustness real-time positioning under the condition of violent illumination change; in a geometrically degraded roadway area, registration positioning of laser point cloud emission fails due to lack of enough external characteristics, and at the moment, the visual positioning module can still work normally and complete robot repositioning by detecting matched image information; in an environment lacking enough illumination, the laser point cloud and acceleration information can still provide enough positioning fusion data input for the computing unit.
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