A Synchronous Data Acquisition System of Inertial Sensor and Visual Sensor

Abstract

The invention discloses an inertial sensor and vision sensor data synchronous acquisition system which comprises a sampling time sequence generation module, a time sequence encoding module and a data acquisition and time sequence binding module, wherein the sampling time sequence generation module is used for generating a base period triggering signal, an inertial data acquisition triggering signal and a vision data acquisition triggering signal; the periods of the inertial and vision data acquisition triggering signals are integral multiple that of the base period triggering signal; the time sequence encoding module is used for maintaining storage units to the three periodic triggering signals respectively and used for synchronizing contents of the storage units corresponding to the inertial and vision data acquisition triggering signals to be contents of a storage unit corresponding to the base period triggering signal; the data acquisition and time sequence binding module is used for adding the contents of maintaining units corresponding to the inertial and vision data acquisition triggering signals after time sequence encoding to received acquisition data of the inertial and vision sensors. By adopting the inertial sensor and vision sensor data synchronous acquisition system, data of the inertial sensor and vision sensors can be synchronously acquired, and errors caused by synchronous data acquisition can be avoided.

Description

technical field [0001] The invention relates to the field of data acquisition and processing of inertial sensors and visual sensors, in particular to a synchronous data acquisition system combining inertial and visual sensors. Background technique [0002] Inertial sensors, as motion sensors with strong autonomy, have been widely used in applications such as motion measurement, navigation and positioning. The inertial navigation system based on inertial sensors can provide all navigation parameters such as position, velocity and attitude. But its positioning error keeps getting bigger with the passage of time. [0003] With the development of various vision sensors, computer vision has been widely used in industry and consumer electronics. Integrating inertial information and visual information to form an inertial + visual navigation and positioning system can further improve the accuracy and reliability of the system. Therefore, it is widely used in fields such as intell...

AI Technical Summary

Problems solved by technology

However, for the highly dynamic movement of the carrier, the error caused by asynchronous measurement will become a major factor affecting the fusion calculation

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