55
You do connect all these sensors directly to a microcontroller.
The Kalman filter is not an electronic filter like a LRC filter that goes between the sensors and the microcontroller. The Kalman filter is a mathematical filter implemented as software routine inside the microcontroller.
The sensors you have listed give the microcontroller 14 or 15 raw numbers ...
30
The short, snide answer is "try it without one." The better answer is an example: When your accellerometers say you are 10 degrees from vertical, but your gyro says you haven't rotated away from vertical, and your magnetometers are reporting a 30 deg offset from north but your gyro says 32 degree ... what is the current heading and tilt?
You'll probably ...
24
Sensor data is noisy. If you do not filter it, then your vehicle would at least act erratically if it were even stable enough to fly. Filtering, via a Kalman filter or otherwise, can reduce the noise when done correctly, improving stability in turn.
A Kalman filter is a particularly powerful filter. It takes a model of the system and noise models for both ...
21
At least in part quadrotors offer a nice balance between the complexity of the dynamics and power requirements. With traditional single rotor helicopters, control is a function of the orientation of the rotor which means you must change its orientation to change direction of the craft. This makes for very complex mechanical linkages comparatively speaking ...
10
You need 4 degrees of freedom to control yaw, pitch, roll and thrust.
Four props is therefore the minimum number of actuators required. Tricoptors require a servo to tilt one or more rotors which is more mechanically complicated.
There is no restriction to only 4 props, hexa+ coptors are also very common.
Generally you want an even number of props unless ...
9
Let's look at how a quadrotor flies, then apply that to a trirotor.
Let's assume that we want to remain in a stationary hover position. To do that, you need to balance all the forces: thrust from the propellers vs. gravity, and the torques of each motor.
Each motor produces both thrust and torque according to the equations:
$$
T = K_T\rho n^2 D^4
$$
$$
Q = ...
9
A Kalman Filter is an algorithm that is commonly used in UAVs to fuse multiple sensor measurements together to provide an "optimal" estimate of the position and/or orientation of the UAV. For example, a Kalman Filter can fuse accelerometer, gyro and magnetometer measurements with a velocity estimate to estimate the UAV's yaw, pitch and roll.
For more ...
9
You could use particle filters as well. For the basic intro to Particle Filters, you could have a look at Professor Thrun's videos in Programming a Robotic Car.
http://www.youtube.com/watch?v=H0G1yslM5rc
http://www.youtube.com/watch?v=QgOUu2sUDzg
Particle filters are more robust and have a far lesser probability of the loop closure error, which commonly ...
9
Generally engineers implement dual, triple or more sensors with the same function for one or more of the following reasons:
Reliability: the system should be reliable. Several values can be fetched from several sensor. A voter decides the output(final) value. Boing 777 has 6 sensors for each function.
Safety and critical systems: if one sensor fails, ...
8
I think your question is a bit too open-ended. To get more specific recommendations, I think you'd have to provide some idea of what facet of robotics you want to get involved in. The mechanical buildling aspect? Motor control? Microcontroller programming? Use of various sensors? As an example, I can ask what do you mean by powerful in your question ... ...
6
Re-implementing your solution, I get this:
Angle Between Vectors
First, you want the angle between points $A$ and $B$ -- not specifically the unit vector.
(via Fx Programming):
$\theta = math.atan2(B_{x}-A_{x}, B_{y}-A_{y})$
Vehicle Yaw Angle
Next (and I suspect this is your problem), you need to subtract the vehicle's yaw angle $\psi$ from your ...
5
Am I correct in saying that this would not require a gyro, just a 3 (2?) axis accelerometer, to detect pitch and roll, then adjust the ailerons and elevator to compensate?
No. The opposite is true. The accelerometer will be almost useless to detect rotations on a platform that's experiencing unknown accelerations. Your plane will be subject to two force ...
5
As the name of the accelerometer implies, you measure the acceleration on your system excluding that from the gravitational force. When your sensor is at rest, you measure the acceleration from the force that you use to counteract the gravitational force. This is how you can fix your orientation vs the gravity vector. When the sensor is accelerated, as would ...
5
I'll assume you're talking about a 3D vector here. Can you just generalize normalize() like that? Is it that common (i've never seen it so if it is, then news to me). Otherwise, obvious compass wrap issues apply to each of the X and Y components. Why not call them roll and/or pitch and/or yaw? (mixing 3D and 2D nomenclature confuses the question).
My 2D ...
5
How close together? If they use the same make and model GPS unit, you MIGHT be able to use the relative positions calculated via GPS. A lot of the sources of GPS error would be the same for both vehicles in that case (e.g., atmospherics, any built-in GPS filtering). Each vehicle could broadcast it's state vector to the other one.
5
The signals to the ESC's using PWM should be sent after the PID algo is done processing the errors. The output calculated from the PID is the PWM value to be sent to the ESC's to actuate the motors in such a way that they move to reduce the error thus obtaining the desired orientation
So the right order is:
Read RX signal
Calculate desired pitch, roll, ...
4
I think the main reason is that they're simply easier to build in a stable way. A 120º angle is harder to get right than a 90º angle.
Another thing that is a little easier to understand is how the relationship between propellers leads to different types of motion. Thinking about different propellers moving at different speeds and directions and how that ...
4
It is possible that two independent GPS units might be accurate enough (as ViennaMike suggests) if both are sufficiently similar, get a lock from the same location, follow roughly the same paths (so the accumulated differential GPS errors are roughly the same) and are re-synchronised at regular intervals.
This might be significantly assisted though if you ...
4
Not all fixed wing aircraft are inherently instable. That feature greatly depends on the center pressure and gravity center designed position. Passenger aircrafts are quite stable, and fight planes are just the opposite in order to achieve fast maneouvres, among other reasons.
Read this aviation thread where this question was replied.
4
The component you highlighted is called a tensile load cell. You could buy one from a supplier, but it probably would be cheaper to buy a cheap digital hanging scale and taking the sensor out of it - at least I couldn't find one less than $100, ten times the price of a 50kg digital hanging scale.
You will need to do some analog conversion and amplification ...
3
The mechanical answers above are correct. The inherent stability problems with single large motors are exchanged for dynamic comtrol over 12 dimensions of acceleration, yaw, pitch, roll which can be partially coupled (the translational amd rotational matrix) where one is presented with a simplified diagonal inertial frame to build a dynamic model with. In ...
3
How close together is important. I saw the range of 0-5m, but if you're suggesting that they might touch, or just barely not touch, then you're going to have difficulties. Lightweight is also a vague term which will need to be defined better in order to adequately answer your question. Still, there are some things to keep in mind:
Augmented GPS can get you ...
3
This was on rcgroups:
Reply by Rob_Lefebvre on December 31, 2014 at 7:02am
Here is a brief history:
The APM class boards used the MPU6000 gyro/accel chip.
The Pixhawk was originally designed to use the LSM303D chip, as it was supposed to be better.
Initial prototype testing of Pixhawk boards revealed problems with the LSM chip. To avoid ...
3
Both the solutions you proposed do suffer from unwanted interaction among the two PIDs. You're basically trying to assign two simultaneous goals - i.e. final relative position along with terminal non null speed - when the system has only one input variable, let's say the "thrust" driving the UAV dynamics.
The correct scheme should be the one depicted below:
...
3
This will depend on what you mean by "displacement" and for how long you want to do this. Can you supply more details on what your trying to accomplish and why?
As Bending Unit 22 mentioned, you integrate acceleration to get velocity, and then integrate velocity to get position. The problem with this though that any drift/error/noise on the ...
3
Matlab has a package called Simscape that you can use for modeling physical systems in general. I would just caution you up front that Simscape is almost more like a plugin manager in that it enables other modules and doesn't offer a terrific amount of content on its own. This means you get to buy Simscape, then buy whatever other toolboxes you want that ...
3
This thing is generally called coverage path planning.
If you are particularly interested in Boustrophedon Cell Decomposition, you may have a look at the paper introducing it: Choset and Pignon (1998).
You may also want to check out this survey paper.
2
6-DOF is kind of difficult.. You could do vision but that is hard to implement robustly. You say the UAVs are localizing themselves using GPS; are you using an IMU+Kalman filtering as well? For proximity detection you could try infrared/ultrasonic sensors, e.g. https://www.sparkfun.com/products/242. You could combine this with the Kalman filter to get a ...
2
Get a LEGO NXT kit, it costs around $280, and will give you a lot of fun.
You can control it from your computer using any programming language - just send Bluetooth commands to the LEGO NXT brick. It is very simple!
If you want to learn more - here is a simple KB article about that: http://www.robotappstore.com/Knowledge-Base/Introduction-To-Lego-NXT-...
2
Arduino is a great fit for your problem. It is not only used by hobbyists and beginners but it is frequently used by top Universities for both teaching and in research. Arduino also has a large active community which makes helps when you have a problem.
There are a couple of caveats to the Arduino solution however. 1) They have very limited computational ...
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