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In this Article we will describe AMLS project, namely, AMLS Optical stabilization, GPS holding, GPS following, Altitude holding, grapling system and Weather protection system, illumination and speed measurment system. Plus we will make clear how it works and how it's done!
https://github.com/XxOinvizioNxX/Liberty-Way
- Pavel Neshumov: xxoinvizionxx@gmail.com
- Andrey Kabalin: astik452@gmail.com
- Vladislav Yasnetsky: vlad.yasn@gmail.com
- 0. How it works?
- 1. GPS hold and Flight to waypoints functions
- 2. GPS following
- 3. Compass
- 4. Altitude stabilization (barometer)
- 5. Optical stabilization
- 6. Eitude AMLS Platform
- 7. Conclusion
The AMLS system consists of two parts:
- Drone
- And the platform either mobile (implemented on a vehicle), either stable (pick-up-point)
How the system operates:
- Firstly, drone with a delivery is far from the platform without visual contact with it. Drone recieves GPS coordinates of a platform by using cellular communication or any other radio channel (Drone has Liberty-Link implemented on it,this module is able to adjust its position, whatever the firmware of flight controller. Module is installed in line break from receiver to flight controller.
- Drone is moving to coordinates. Coordinateds might be renewed in the process (but not frequently, to prevent channel from overload)
- When drone is close to the platform but there is still no visual contact, program runs GPS stabilization. In this regard data it beeing trunsmited by closest radio connetion on high freqency, so the drone can catch up with the platform.
- Meanwhile, Drone decends (barometers are installed on both drone and platform). Descending goes on till 1.5-2 meter height above the platform.
- While descending and when visual contact with platform camera is established program enables visual (precision) stabilization. And as soon as drone's tag is within camera's field of view algorithm will capture the drone.
- When optical stabilization is enabled, GPS works for back up plan (in case when something goes wrong GPS stabilization starts again).
- In order to use optical stabilization drone is implemented with ARUCO tag which can be captured by camera and by using closest radio communication, system transmits adjustment data to drone.
- Along with optical stabilization, program launches landing. The algorithm artificially smoothly reduces setpoint of hight (Z) to some kind of threshold.
- When drone is approaching on needed height, Program enables grabbing system implemented on platform,those grips are used to catch and hold the drone while and after landing.
- After landing is complite,platform starts maintenance work and in order to protect the drone frome external influence, program enables weather protection and closes the roof above landing area.
- Landing accomplished!
Short video about our project (clickable):
.png)
As stated earlier, drone is implemented with "universal" module Liberty-Link, receiving commands from platform and adjusting drone position, intervening in remote control signal (More in the following paragraphs).
GPS module will be built in Liberty-Link, so is ability to maintain and follow GPS points.
The result of the GPS hold algorithm (clickable):
.png)
GPS-module will be from the UBlox group (for instance, UBlox Neo-M8). There are will be 1 or 3 (to minimize the error) modules.
Modules operate via UART, configured to send 5 times per second. The Liberty-Link firmware will read data from the modules and calculate the coordinates of the current position.
Reading data from a module into a buffer looks like this:
// Read data from the GPS module
while (GPS_serial.available() && new_line_found == 0) {
// Stay in this loop as long as there is serial information from the GPS available
char read_serial_byte = GPS_serial.read();
if (read_serial_byte == '$') {
// Clear the old data from the incomming buffer array if the new byte equals a $ character
for (message_counter = 0; message_counter <= 99; message_counter++) {
incomming_message[message_counter] = '-';
}
// Reset the message_counter variable because we want to start writing at the begin of the array
message_counter = 0;
}
// If the received byte does not equal a $ character, increase the message_counter variable
else if (message_counter <= 99)
message_counter++;
// Write the new received byte to the new position in the incomming_message array
incomming_message[message_counter] = read_serial_byte;
// Every NMEA line end with a '*'. If this character is detected the new_line_found variable is set to 1
if (read_serial_byte == '*') new_line_found = 1;
}After, latitude, longitude, type of correction are calculated from the filled buffer(2D, 3D) and the number of satellites. Parsing GPS data of the UBlox protocol looks like this:
// If the software has detected a new NMEA line it will check if it's a valid line that can be used
if (new_line_found == 1) {
// Reset the new_line_found variable for the next line
new_line_found = 0;
if (incomming_message[4] == 'L' && incomming_message[5] == 'L' && incomming_message[7] == ',') {
// When there is no GPS fix or latitude/longitude information available
// Set some variables to 0 if no valid information is found by the GPS module. This is needed for GPS lost when flying
l_lat_gps = 0;
l_lon_gps = 0;
lat_gps_previous = 0;
lon_gps_previous = 0;
number_used_sats = 0;
}
// If the line starts with GA and if there is a GPS fix we can scan the line for the latitude, longitude and number of satellites
if (incomming_message[4] == 'G' && incomming_message[5] == 'A' && (incomming_message[44] == '1' || incomming_message[44] == '2')) {
// Filter the minutes for the GGA line multiplied by 10
lat_gps_actual = ((int)incomming_message[19] - 48) * (long)10000000;
lat_gps_actual += ((int)incomming_message[20] - 48) * (long)1000000;
lat_gps_actual += ((int)incomming_message[22] - 48) * (long)100000;
lat_gps_actual += ((int)incomming_message[23] - 48) * (long)10000;
lat_gps_actual += ((int)incomming_message[24] - 48) * (long)1000;
lat_gps_actual += ((int)incomming_message[25] - 48) * (long)100;
lat_gps_actual += ((int)incomming_message[26] - 48) * (long)10;
// To convert the minutes to degrees we need to divide the minutes by 6
lat_gps_actual /= (long)6;
// Add the degrees multiplied by 10
lat_gps_actual += ((int)incomming_message[17] - 48) * (long)100000000;
lat_gps_actual += ((int)incomming_message[18] - 48) * (long)10000000;
// Divide everything by 10
lat_gps_actual /= 10;
// Filter the minutes for the GGA line multiplied by 10
lon_gps_actual = ((int)incomming_message[33] - 48) * (long)10000000;
lon_gps_actual += ((int)incomming_message[34] - 48) * (long)1000000;
lon_gps_actual += ((int)incomming_message[36] - 48) * (long)100000;
lon_gps_actual += ((int)incomming_message[37] - 48) * (long)10000;
lon_gps_actual += ((int)incomming_message[38] - 48) * (long)1000;
lon_gps_actual += ((int)incomming_message[39] - 48) * (long)100;
lon_gps_actual += ((int)incomming_message[40] - 48) * (long)10;
// To convert the minutes to degrees we need to divide the minutes by 6
lon_gps_actual /= (long)6;
// Add the degrees multiplied by 10
lon_gps_actual += ((int)incomming_message[30] - 48) * (long)1000000000;
lon_gps_actual += ((int)incomming_message[31] - 48) * (long)100000000;
lon_gps_actual += ((int)incomming_message[32] - 48) * (long)10000000;
// Divide everything by 10
lon_gps_actual /= 10;
if (incomming_message[28] == 'N')
// When flying north of the equator the latitude_north variable will be set to 1
latitude_north = 1;
else
// When flying south of the equator the latitude_north variable will be set to 0
latitude_north = 0;
if (incomming_message[42] == 'E')
// When flying east of the prime meridian the longiude_east variable will be set to 1
longiude_east = 1;
else
// When flying west of the prime meridian the longiude_east variable will be set to 0
longiude_east = 0;
// Filter the number of satillites from the GGA line
number_used_sats = ((int)incomming_message[46] - 48) * (long)10;
number_used_sats += (int)incomming_message[47] - 48;
if (lat_gps_previous == 0 && lon_gps_previous == 0) {
// If this is the first time the GPS code is used
// Set the lat_gps_previous variable to the lat_gps_actual variable
lat_gps_previous = lat_gps_actual;
// Set the lon_gps_previous variable to the lon_gps_actual variable
lon_gps_previous = lon_gps_actual;
}
// Divide the difference between the new and previous latitude by ten
lat_gps_loop_add = (float)(lat_gps_actual - lat_gps_previous) / 10.0;
// Divide the difference between the new and previous longitude by ten
lon_gps_loop_add = (float)(lon_gps_actual - lon_gps_previous) / 10.0;
// Set the l_lat_gps variable to the previous latitude value
l_lat_gps = lat_gps_previous;
// Set the l_lon_gps variable to the previous longitude value
l_lon_gps = lon_gps_previous;
// Remember the new latitude value in the lat_gps_previous variable for the next loop
lat_gps_previous = lat_gps_actual;
// Remember the new longitude value in the lat_gps_previous variable for the next loop
lon_gps_previous = lon_gps_actual;
}
// If the line starts with SA and if there is a GPS fix we can scan the line for the fix type (none, 2D or 3D)
if (incomming_message[4] == 'S' && incomming_message[5] == 'A')
fix_type = (int)incomming_message[9] - 48;
}Then, when needed data is received main magic happens. To enable maintaining of the current position will be enough to set the flag waypoint_set = 1; and set current coordinates as waypoint:
l_lat_waypoint = l_lat_gps;
l_lon_waypoint = l_lon_gps;After that, the calculation of the error in the coordinates will begin, correction works with help of PD - regulator. For D - component we use rotation memory.
If you just set the new l_lat_waypoint and l_lon_wayoint, which are located at a great distance from the drone, the drone will not be able to fly normally and stabilize at these coordinates. For smooth adjustments l_lat_gps_float_adjust and l_lon_gps_float_adjust can be used. These are float variables, changing which will smoothly shifts l_lat_waypoint and l_lon_waypoint.
For example, if in the main loop you will constantly add a certain value to these variables:
l_lat_gps_float_adjust += 0.0015;With setted waypoint, the drone will move smoothly in the given direction. In the future, this will be used for smooth acceleration and deceleration while moving to the point.
if (waypoint_set == 1) {
//If the waypoints are stored
// Adjust l_lat_waypoint
if (l_lat_gps_float_adjust > 1) {
l_lat_waypoint++;
l_lat_gps_float_adjust--;
}
if (l_lat_gps_float_adjust < -1) {
l_lat_waypoint--;
l_lat_gps_float_adjust++;
}
// Adjust l_lon_waypoint
if (l_lon_gps_float_adjust > 1) {
l_lon_waypoint++;
l_lon_gps_float_adjust--;
}
if (l_lon_gps_float_adjust < -1) {
l_lon_waypoint--;
l_lon_gps_float_adjust++;
}
// Calculate the latitude error between waypoint and actual position
gps_lon_error = l_lon_waypoint - l_lon_gps;
// Calculate the longitude error between waypoint and actual position
gps_lat_error = l_lat_gps - l_lat_waypoint;
// Subtract the current memory position to make room for the new value
gps_lat_total_avarage -= gps_lat_rotating_mem[gps_rotating_mem_location];
// Calculate the new change between the actual pressure and the previous measurement
gps_lat_rotating_mem[gps_rotating_mem_location] = gps_lat_error - gps_lat_error_previous;
// Add the new value to the long term avarage value
gps_lat_total_avarage += gps_lat_rotating_mem[gps_rotating_mem_location];
// Subtract the current memory position to make room for the new value
gps_lon_total_avarage -= gps_lon_rotating_mem[gps_rotating_mem_location];
// Calculate the new change between the actual pressure and the previous measurement
gps_lon_rotating_mem[gps_rotating_mem_location] = gps_lon_error - gps_lon_error_previous;
// Add the new value to the long term avarage value
gps_lon_total_avarage += gps_lon_rotating_mem[gps_rotating_mem_location];
// Increase the rotating memory location
gps_rotating_mem_location++;
if (gps_rotating_mem_location == 35)
// Start at 0 when the memory location 35 is reached
gps_rotating_mem_location = 0;
// Remember the error for the next loop
gps_lat_error_previous = gps_lat_error;
gps_lon_error_previous = gps_lon_error;
//Calculate the GPS pitch and roll correction as if the nose of the multicopter is facing north.
//The Proportional part = (float)gps_lat_error * gps_p_gain.
//The Derivative part = (float)gps_lat_total_avarage * gps_d_gain.
gps_pitch_adjust_north = (float)gps_lat_error * gps_p_gain + (float)gps_lat_total_avarage * gps_d_gain;
gps_roll_adjust_north = (float)gps_lon_error * gps_p_gain + (float)gps_lon_total_avarage * gps_d_gain;
if (!latitude_north)
// Invert the pitch adjustmet because the quadcopter is flying south of the equator
gps_pitch_adjust_north *= -1;
if (!longiude_east)
// Invert the roll adjustmet because the quadcopter is flying west of the prime meridian
gps_roll_adjust_north *= -1;
//Because the correction is calculated as if the nose was facing north, we need to convert it for the current heading.
gps_roll_adjust = ((float)gps_roll_adjust_north * cos(angle_yaw * 0.017453)) + ((float)gps_pitch_adjust_north * cos((angle_yaw - 90) * 0.017453));
gps_pitch_adjust = ((float)gps_pitch_adjust_north * cos(angle_yaw * 0.017453)) + ((float)gps_roll_adjust_north * cos((angle_yaw + 90) * 0.017453));
//Limit the maximum correction to 300. This way we still have full controll with the pitch and roll stick on the transmitter.
if (gps_roll_adjust > 300) gps_roll_adjust = 300;
if (gps_roll_adjust < -300) gps_roll_adjust = -300;
if (gps_pitch_adjust > 300) gps_pitch_adjust = 300;
if (gps_pitch_adjust < -300) gps_pitch_adjust = -300;
}
The main part of stabilization using GPS coordinates was the development of an algorithm for predicting the position of the drone. The simplest idea is to use a mathematical calculation of the next drone position. This is calculated for the most accurate positioning in relation to the landing platform.
At the beginning we developed a simple algorithm for calculating the coefficient of coordinate change. Development was done using Python. At the stage of testing this algorithm, the problem of simulating the generation of GPS coordinates arose. To solve this problem, many different resources were used: from open source homemade navigators to trying to use the Google Maps API, Yandex Maps or 2GIS. And only after a 3 month, we thought of a simple change of values for some delta with drawing in MatPlotLib or PyQtGraph. Prior to this, all testing of the algorithm was carried out using the PX4 firmware toolkit, the Gazebo drone motion simulator. As a result, many formalities were overcome in terms of communicating with the simulator and increasing productivity(click on picture to see the video).
The result of the GPS prediction (clickable):
.png)
The end result is an error in the predicted boundaries of the range from 0 to 70 centimeters.
Before optical stabilization (during GPS stabilization), to calculate the GPS correction vector, you need to know the exact angle from the compass. For this, a compass built into the GPS module is used.
Because during the flight, the roll and pitch angles change, you need to correct the values from the compass. In general, calculating the angle from a computer looks like this:
// The compass values change when the roll and pitch angle of the quadcopter changes. That's the reason that the x and y values need to calculated for a virtual horizontal position
// The 0.0174533 value is phi/180 as the functions are in radians in stead of degrees
compass_x_horizontal = (float)compass_x * cos(angle_pitch * -0.0174533) + (float)compass_y * sin(angle_roll * 0.0174533) * sin(angle_pitch * -0.0174533) - (float)compass_z * cos(angle_roll * 0.0174533) * sin(angle_pitch * -0.0174533);
compass_y_horizontal = (float)compass_y * cos(angle_roll * 0.0174533) + (float)compass_z * sin(angle_roll * 0.0174533);
// Now that the horizontal values are known the heading can be calculated. With the following lines of code the heading is calculated in degrees.
// Please note that the atan2 uses radians in stead of degrees. That is why the 180/3.14 is used.
if (compass_y_horizontal < 0)actual_compass_heading = 180 + (180 + ((atan2(compass_y_horizontal, compass_x_horizontal)) * (180 / 3.14)));
else actual_compass_heading = (atan2(compass_y_horizontal, compass_x_horizontal)) * (180 / 3.14);
// Add the declination to the magnetic compass heading to get the geographic north
actual_compass_heading += declination;
// If the compass heading becomes smaller then 0, 360 is added to keep it in the 0 till 360 degrees range
if (actual_compass_heading < 0) actual_compass_heading += 360;
// If the compass heading becomes larger then 360, 360 is subtracted to keep it in the 0 till 360 degrees range
else if (actual_compass_heading >= 360) actual_compass_heading -= 360;It is clear that the angle from the compass can also be used to maintain the yaw angle of the drone as a whole. With point-to-point flights, this may be realized. But at the moment, there is no urgent need for this, because after the start of optical stabilization, its algorithm is able to correct the drone regardless of its yaw angle. Also, during optical stabilization, the yaw angle is automatically corrected.
Before optical stabilization (during GPS stabilization), Our Liberty-Link module will be able to maintain altitude using a barometer.
The platform, as well as the Liberty-Link, will have MS5611 barometers
According to the documentation, the height resolution is 10cm. The algorithm will take the pressure values and by passing it through the PID controller will stabilize the drone's altitude by changing the Throttle (3rd channel).
Altitude hold test (clickable):
During the flight along the waypoint, the setpoint of the pressure will decrease in order to increase the altitude (it is safer to fly in a straight line at a high altitude, so as not to crash into anything). And during GPS stabilization (when the drone is already close to the platform), the drone will be set to a pressure setpoint such that it corresponds to ~ 1.5-2m height above the platform.
Optical stabilization is the most important and challenging part of our project. Only using this algorithms, in our conditions, it is possible to keep the drone above the platform stand and still. The current version of the OIS algorithm, along with a description for repeat, is available in our main GitHub repository. In the future, GPS stabilization will be added to it.
And as we couldn't predict the possibility of accomplishing of our task, first of all, we started to think about means for stabilization system. Afterwards, we stopped on stabilazing using augmented reality tags. Firstly, it won't take much finances as GPS or RTK systems and will be accurate enough to accomplish it's purpose. Our first idea was to attach Raspberry Pi with Liberty_X as it's made in COEX Clover and give all the stabilization math to Raspberry Pi.
First optical stabilization prototype test (Сlickable):
.png)
But few tests shown that Raspberry Pi computing power is not enough for amount of data needed to stabilize the drone. Furthermore, the idea of installing a Raspberry Pi on each drone is irrational for its own.
Also, we had intermediate prototypes, for example, attempts to use color markers (circles of different colors), but these ideas did not work well enough.
Then we came up with idea of separating drone and stabilization system so the main math will be accomplished on landing platform with powerful machine.
To highlight the platform we took 4 ARUCO tags and as for recognition we've used as OpenCV algorithms. But in first version of stabilization we didn't have any defining algorithms for markers in space.
(clickable)
.png)
Then, we came up with using Pose Estimation algorithms from OpenCV library. The first tests showed that we are on the right track!
Pose Estimation Pyhton (Clickable):
.png)
But, the algorithms were far from ideal. For example, since the code was written in Python (https://github.com/XxOinvizioNxX/Liberty-X_Point), the performance was not great, and there was no normal flow control either. Therefore, we had to change something.
Having weighed all the pros and cons, it was decided to rewrite all optical stabilization in Java. This is how the first version of Liberty-Way appeared. This time, it was decided to approach the OOP thoroughly, and, after a little tweaking, an excellent stabilization and landing algorithm was obtained.
Landing test on Liberty-Way v.beta_0.0.1 (clickable):
.png)
That was followed by many improvements and bug fixes. As a result, Liberty-Way is a cross-platform web sarvar application that is very convenient for configuration and debugging. Also, in the latest versions (beta_1.0.3 - beta_1.1.2) blackbox was introduced (for recording logs), as well as communication with the platform and many other necessary algorithms.
Full description, including all settings, startup, etc. you can find it in our GitHub repository: https://github.com/XxOinvizioNxX/Liberty-Way
Video of static stabilization (clickable):
.png)
Liberty-Way can even stabilize a "thrown" drone (clickable):
There is a small bug in the video with the rotation angle, in the new release it has been fixed
And, of course, work in motion (tested for beta_0.0.3) (clickable):
.png)
All basic settings are conveniently placed in separate JSON files (settings, pid), which allows you to quickly change the required parameters without rebuilding the application. In fact, to run the application, you just need to download the latest release, unpack the archive and run it through the launcher corresponding to your OS.
The Liberty-Way connects to the Liberty-Link module installed on the drone and adjusts its position by directly controlling four main channels of the remote control. In one cycle (each frame from the camera), 12 bytes of correction data are sent to the module:
Bytes description:
- Roll bytes - Roll correction values
- Pitch bytes - Pitch correction values
- Yaw bytes - Yaw correction values
- Altitude bytes - Altitude correction values
- Service info - sets the drone state (0 - Nothing to do, 1 - Stabilization, 2 - Landing (command not implemented and will be removed in the future. This is not a real landing, just to tell the drone to start decreasing altitude), 3 - Disable motors)
- Check byte - XOR sum of all previous bytes that is compared via transmittion in order to verify the data
- Data suffix - unique pair of ASCII symbols that is not represented in the packet in any form and that shows the end of the packet
On the drone side (Liberty-Link module), data reading is as follows:
while (Telemetry_serial.available()) {
tdc_receive_buffer[tdc_receive_buffer_counter] = Telemetry_serial.read();
if (tdc_receive_byte_previous == 'L' && tdc_receive_buffer[tdc_receive_buffer_counter] == 'X') {
tdc_receive_buffer_counter = 0;
if (tdc_receive_start_detect >= 2) {
tdc_check_byte = 0;
for (tdc_temp_byte = 0; tdc_temp_byte <= 8; tdc_temp_byte++)
tdc_check_byte ^= tdc_receive_buffer[tdc_temp_byte];
if (tdc_check_byte == tdc_receive_buffer[9]) {
direct_roll_control = (uint32_t)tdc_receive_buffer[1] | (uint32_t)tdc_receive_buffer[0] << 8;
direct_pitch_control = (uint32_t)tdc_receive_buffer[3] | (uint32_t)tdc_receive_buffer[2] << 8;
direct_yaw_control = (uint32_t)tdc_receive_buffer[5] | (uint32_t)tdc_receive_buffer[4] << 8;
direct_throttle_control = (uint32_t)tdc_receive_buffer[7] | (uint32_t)tdc_receive_buffer[6] << 8;
direct_service_info = (uint32_t)tdc_receive_buffer[8];
if (direct_roll_control > 1100 && direct_roll_control < 1900 &&
direct_pitch_control > 1100 && direct_pitch_control < 1900 &&
direct_yaw_control > 1100 && direct_yaw_control < 1900 &&
direct_throttle_control > 1100 && direct_throttle_control < 1900 &&
/*flight_mode == 2 &&*/ channel_7 > 1500) {
tdc_timer = millis();
tdc_working = 1;
}
else
tdc_working = 0;
}
else {
direct_roll_control = 1500;
direct_pitch_control = 1500;
tdc_working = 0;
}
} else
tdc_receive_start_detect++;
}
else {
tdc_receive_byte_previous = tdc_receive_buffer[tdc_receive_buffer_counter];
tdc_receive_buffer_counter++;
if (tdc_receive_buffer_counter > 11)tdc_receive_buffer_counter = 0;
}
}
if (millis() - tdc_timer >= 500) {
tdc_working = 0;
}
if (tdc_working && direct_service_info == 2 && !return_to_home_step)
return_to_home_step = 3;
if (!tdc_working)
return_to_home_step = 0;
if (!tdc_working || direct_service_info < 1) {
direct_roll_control = 1500;
direct_pitch_control = 1500;
direct_yaw_control = 1500;
direct_throttle_control = 1500;
}As a result, there are 4 variables:
direct_roll_control
direct_pitch_control
direct_yaw_control
direct_throttle_control
Which are directly added to the data received from the control panel. Probably, in the future, other data will be added, at least for working with GPS. Stay tuned for updates in our repository.
To operate our system in real conditions, it is required to minimize camera shaking if we don't want to lose the tag on the drone. In this regard, a 3D model of attaching the gimbal from the drone to our platform was developed to stabilize a conventional webcam.
Camera mount:
Attaching the wire (ferrite filter on the wire) of the camera:
Fastening the "crabs" latches on the suspension substrate:
An approximate view of the assembly of the entire suspension mechanism:
The platform is an interconnected system for landing a drone. The platform is planned to be controlled via the Serial interface, using the G-Code commands: The current platform code can be found in the Eitude GitHub repository: https://github.com/XxOinvizioNxX/Eitude
As you may know it doesn't matter how good is our stabilization but without grabbing system drone will crush eventually. In this regard we developed a 3D model of a grabbing system with 4 grips with hook in the end of each one this will allow to slowly grab the drone while it lands and hold it in place after landing.
As for the weather protection we developed a 3D model to create a roof that will protect the drone from weather conditions while it is on the platform. The AMLS roof mechanism is a scissor mechanism covered with a tarpaulin, which are located on the edges of the platform and after a successful landing, the mechanisms on both sides of the platform will close and protect the drone from external influences. The roof structure itself makes it quite light and strong, and the scissor mechanism allows you to simply fold and unfold, moreover, the assembly of such a mechanism will be simple and reliable.
For landing on a quickly moving platform, it is very useful to know the speed of its movement. For now, the platform does not have a GPS module, or any other way to measure absolute speed. Therefore, for a temporary solution to this problem, it was decided to calculate the speed from acceleration using an accelerometer. For example, MPU6050. The IMU is mounted on the prototype platform through a soft backing and covered with a cover to protect it from the wind. The stabilization algorithm (Liberty-Way) sends a request to the platform L1 to test the speed. Returns S0 L <speed in km / h>.
Speedometer test (inside the gray circle, lower right parameter (SPD) - speed in km / h) (Clickable):
To calculate the speed, the acceleration is taken for short time periods, then multiplied with time, getting the instantaneous speed. Which is constantly added to the previous amount:
void speed_handler(void) {
gyro_signalen();
// Filter accelerations
acc_x_filtered = (float)acc_x_filtered * ACC_FILTER_KOEFF + (float)acc_x * (1.0 - ACC_FILTER_KOEFF);
speed = acc_x_filtered;
// Convert acceleration to G
speed /= 4096.0;
// Convert to m/s^2
speed *= 9.81;
// Multiply by dt to get instant speed in m/ms
speed *= (millis() - speed_loop_timer);
// Reset timer
speed_loop_timer = millis();
// Convert to m/s
speed /= 1000.0;
// Convert to km/h
speed *= 3.6;
// Accumulate instatnt speed
speed_accumulator += speed;
if (!in_move_flag) {
// If the platform is not moving, reset the speed
speed_accumulator = speed_accumulator * SPEED_ZEROING_FACTOR;
}
}Despite having various filters, due to the error, the speed may not "return" to 0, therefore, vibrations are also measured, and if they are less than the threshold, it is considered that the platform is at a standstill and the speed is gradually reset to zero.
The complete code of the speedometer can be found in the Eitude repository on GitHub: https://github.com/XxOinvizioNxX/Eitude
As our platform must work in various environmental conditions, and optical stabilization is very demanding on the visibility of the ARUco marker, it is important to have an automatic system for measuring the camera exposure by the level of illumination, and, if there is a lack of it, even turn on additional illumination. In the long term, it is planned to use specialized sensors, for example, the BH1750, as light sensors.
In the current version of the prototype, 6 LEDs are used as a light sensor and an ADC built into the microcontroller. The stabilization algorithm (Liberty-Way) sends a request L0 to the platform to check the illumination level. S0 L <luminance> is returned as a response.
Test for determining the level of illumination using LEDs (clickable):
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Exposure adjustment test and additional illumination (clickable):
What do we have, there is a debugged prototype of optical stabilization, GPS holding, altitude stabilization via barometer, Different platforms prototypes and grat amount of 3D models eager to be implemented. The project to automatically land the drone on a moving platform is not yet complete.
Follow the updates:
- On our repository GitHub: https://github.com/XxOinvizioNxX/Liberty-Way
- On our YouTube channel: https://www.youtube.com/channel/UCqN12Jzy-1eJLkcA32R0jdg
In the future, we plan to do much more new and interesting stuff!
Follow the white rabbit!