A VTOL aircraft visual-inertial navigation method and system for degraded motion

By online determination of degenerative motions such as vertical translation and hovering rotation, and by adopting a multi-sensor adaptive fusion and state protection strategy, the navigation failure problem of vertical take-off and landing aircraft during take-off, landing and hovering phases is solved, and highly robust autonomous navigation without external signal dependence is achieved.

CN121916888BActive Publication Date: 2026-07-03AVIC JINCHENG UNMANNED SYST CO LTD
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Patent Information

Application Number
CN202610386285.X
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2026-03-27
Publication Date
2026-07-03
Estimated Expiration
2046-03-27

AI Technical Summary

Technical Problem

Vertical takeoff and landing (VTOL) aircraft experience navigation failures during takeoff, landing, and hovering due to the degradation of observability of visual inertial odometry. This is especially true in downward-looking configurations and specific motion modes, where existing solutions suffer from signal rejection and safety hazards when relying on external signals.

Method used

By online determination of degenerative motions such as vertical translation and hovering rotation, and by adopting a multi-sensor adaptive fusion and state protection strategy, including sensor data synchronization and preprocessing, degradation mode determination and observability assessment, and adaptive state filtering, autonomous navigation is achieved.

Benefits of technology

In the absence of external signals, the autonomous suppression of navigation divergence improves the navigation robustness and safety of vertical take-off and landing aircraft during critical phases, and solves the observability degradation problem of visual inertial odometry.

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Abstract

This invention discloses a visual inertial navigation method and system for VTOL aircraft with degraded motion. The method includes: Step S1, simultaneously acquiring and preprocessing data from a downward-looking camera, IMU, and barometer; Step S2, online determination of whether the motion of the VTOL aircraft causes visual inertial odometry observability degradation, identifying the degradation mode, and quantifying and evaluating scale observability and translation observability; Step S3, based on a multi-state constrained Kalman filter framework, adaptively executing corresponding information fusion strategies to perform state estimation according to the degradation mode and observability, and outputting navigation state information. The method and system of this invention solve the problem of visual inertial navigation failure under motion modes with observable degradation, and can improve the navigation robustness of VTOL aircraft in critical phases such as takeoff, landing, and hovering under denied environments.
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