Multi-sensor time synchronization

Problems

There are differences in the time recorded by different sensors. If synchronization is not performed, the fusion result will be abnormal. This is the trajectory after I visualized it, and there is a large amount of jitter.

Unsynchronized imu and gps fused

gps track

Possible solutions

In ROS, it is very important to achieve time synchronization of multiple sensors to ensure that sensor data is consistent in time for effective data fusion and processing. Here are some ways to achieve multi-sensor time synchronization:

• Using the message_filters package: message_filters is a package in ROS used to synchronize and filter messages. You can use it to achieve time synchronization of multiple sensor data. You can synchronize messages from different sensors by creating a time synchronizer to ensure that their timestamps are close.

• Use hardware synchronization: If your sensor supports hardware synchronization, you can use hardware synchronization to ensure that the sensor data is synchronized at the hardware level. This can be implemented in hardware circuitry, for example via trigger signals or synchronization lines.

• Use the timestamp alignment algorithm: If your sensor does not support hardware synchronization, you can use the timestamp alignment algorithm to calibrate the sensor's timestamp. This can be achieved by calculating the time offset between different sensors. You can use statistical methods, such as least squares, to estimate the time offset.

• Using the tf library: The tf library is a library in ROS used to handle coordinate transformations. You can use the tf library to synchronize coordinate systems between different sensors and transform sensor data into a common coordinate system.

• Using an external time synchronization device: Some sensors may be equipped with an external time synchronization device, such as a GPS time synchronization module. These devices can be used to ensure that the timestamps of sensor data are synchronized with external time.

• Correct nodes using timestamps: Create a ROS node, subscribe to data from different sensors, and correct based on their timestamps. You can interpolate sensor data in this node to make them consistent in time.