Indoor SLAM map construction method and system

By introducing a global observation benchmark from an environmental camera and a dynamic target elimination mechanism into the indoor SLAM system, the problems of local blind spots and cumulative errors in complex indoor scenes of traditional SLAM are solved, achieving high-precision and robust 3D map construction, which is suitable for automated warehousing operations in densely shelved and dynamic environments.

CN121577019AActive Publication Date: 2026-02-27ZHEJIANG BEITAI INTELLIGENT TECH CO LTD
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Patent Information

Application Number
CN202610098518.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-01-26
Publication Date
2026-02-27
Estimated Expiration
2046-01-26

AI Technical Summary

Technical Problem

Existing indoor SLAM technology faces challenges in indoor environments such as warehouses with dense shelving, narrow aisles, and frequent personnel and equipment movement. These challenges include limited sensor field of view leading to local blind spots, difficulties in identifying dynamic features, and the inability to suppress cumulative errors. These limitations restrict its application in high-precision, high-reliability automated warehousing operations.

Method used

By establishing coordinate transformation relationships between the robot's onboard visual sensors and indoor environmental cameras, and using the environmental cameras to acquire global images to extract static features and construct a global landmark database, combined with dynamic target recognition and elimination mechanisms, multi-source data fusion and backend optimization are performed to generate a high-precision, highly consistent indoor 3D map.

Benefits of technology

It achieves high-precision and high-consistency real-time map construction in complex indoor environments, enhances map integrity and robustness, significantly suppresses cumulative drift, and improves the system's positioning and navigation reliability.

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Abstract

The invention provides an indoor SLAM map construction method and system, and relates to the technical field of image processing, and the construction method comprises the steps: building a unified global space reference through cross-device space-time calibration, supplementing the visual blind area information of a robot in real time through the global static features extracted by an environment camera, and obtaining the visual blind area information of the robot; and meanwhile, dynamic interference features are accurately eliminated in combination with continuous frame analysis, and finally, the pose of the robot is continuously corrected by taking global features as anchor point constraints in back-end optimization. The complete technology chain enables the constructed indoor three-dimensional map to have higher integrity, precision and consistency, significantly improves the positioning robustness and navigation reliability of the robot in an environment with dense goods shelves and dynamic activities, reduces the performance dependence on a robot body sensor and the scene reconstruction cost, and improves the reliability of the robot. And a stable and efficient environment sensing basis is provided for automatic operation of industries such as storage and archive management.
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