Technology Sharing | GPS UAV cluster position autonomous deviation correction function upgrade

The new year is a new beginning, here, I wish you more harvest in the new year, there is better development.

In the New Year, everyone will buy new clothes to wear, and our GPS drone swarm kit will also have new features.

Recently, we have upgraded and optimized the GPS UAV cluster kit to improve and optimize the problem that the data coordinate system of the UAV cluster location is not uniform under outdoor GPS/RTK positioning.

First of all, let's briefly introduce this problem for everyone, mention this problem, we need to understand how the drone uses GPS positioning equipment for positioning, GPS positioning equipment believes that everyone is very familiar, in our daily life is often contacted, mobile phones, cars will be equipped with the device, will tell us the longitude and latitude of the current location of the device.

When the drone is flying outdoors, it will fuse the location data with the drone sensor data to obtain the local location data of the drone, and the gps location data is called global location data.

The local position coordinate system of the drone is NED and ENU (NED in the flight controller, ENU in ROS), in the NED coordinate system, the X axis is due north, the Y axis is due east, the Z axis is down, in the ENU coordinate system, the X axis is due east, the Y axis is due north, and the Z axis is up, and the unit is meters. When we view the positioning data of the drone and control the drone, we generally use the local location coordinate system, and the origin of the local location coordinate system is generally the point where the drone unlocks the take-off as the origin, so when the drone flies to 5 meters high, the position data of the drone is (0, 0, 5).

However, in our UAV cluster system, there will be such a problem, may be doing cluster control, the use of GPS positioning equipment, the UAV does not have a unified coordinate system, the origin of the UAV location data is not at the same point, which will allow us to obtain UAV location data and do cluster control need to do special processing to develop normally.

In the previous program, we are by forcing the UAV to be placed as a zigzag, and there is a uniform interval to achieve the UAV cluster, and this way is obviously not smart enough and autonomous, there are many restrictions in use, not a good solution, we also collected the opinions of many users, hoping to improve this, can achieve random placement of the UAV, but the UAV can automatically adjust the position, to set the formation for flight.

We have also upgraded and optimized for this point, and below we will see the video demonstration of the measured function of our positional autonomy correction function:

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It can be seen in the video that the position autonomous correction effect is still relatively obvious, better, the positioning equipment used in the test is RTK, whether the use of GPS can achieve the effect also needs to be tested, we will also test as soon as possible whether GPS will have the same effect.

This is the end of this issue, we will see you next time!

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