Non-uniform b-spline control point solving method and continuous time positioning method based on adaptive node spacing

By using a non-uniform B-spline method that adaptively adjusts node spacing and control point density, the problems of time alignment error and computational redundancy in multi-sensor fusion positioning are solved, achieving high-precision and efficient positioning results.

CN122284305APending Publication Date: 2026-06-26CHANGSHA UNIVERSITY OF SCIENCE AND TECHNOLOGY
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Patent Information

Application Number
CN202610382792.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-03-26
Publication Date
2026-06-26

AI Technical Summary

Technical Problem

In existing multi-sensor fusion positioning methods, it is difficult to align the data from multiple asynchronous sensors in time, resulting in time registration errors that affect positioning accuracy. Furthermore, the traditional uniform node B-spline method has insufficient fitting ability under complex motion and suffers from severe computational redundancy.

Method used

A non-uniform B-spline control point solution method with adaptive node spacing is adopted. The node spacing is adjusted according to the robot's motion characteristics. The control point density is dynamically adjusted by judging pseudo-acceleration and geometric constraints, thereby optimizing the trajectory model and improving fitting accuracy and computational efficiency.

Benefits of technology

It significantly improves positioning stability and robustness in complex motion scenarios, enhances positioning accuracy and computational efficiency, and closely matches the dynamic motion changes of the robot.

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Abstract

This invention discloses a method for solving control points based on non-uniform B-spline and a continuous-time localization method. It employs a continuous-time domain state representation model and uses non-uniform B-spline with adaptive node spacing as the mathematical basis for trajectory parameterization. Based on this, continuous-time trajectory optimization is performed, which is further subdivided into two key steps: B-spline control point initialization and adaptive sliding window continuous-time trajectory optimization. The method described in this invention can closely adapt to the dynamic motion changes of the robot, and can significantly improve the stability and overall robustness of localization in challenging scenarios with complex motion changes.
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