I have a question. I have a twin-engine boat and I want to implement an autopilot in it. Using GPS alone my boat goes to the destination like a sine wave, unfortunately for 300m. Just like the picture below.
I Use RadioLink M8N GPS SE100 (http://radiolink.com.cn/doce/UploadFile/ProductFile/SE100Manual.pdf) and STM32. It has a built-in geomagnetic sensor HMC5983. Is it possible to use this sensor and GPS to let my boat go straight?
I don't know much about all those Kalman filters, Fusion, etc.
My question is what should I use, apart from the GPS itself, what kind of sensors and filters to make my boat sail in a straight line.
Thanks in advance for the tips and hints.
It is important to position a boat. If you only use poor GPS receiver, you couldn't do this. In order to solve this, you should apply UKF(unscented kalman filter) with fusion of GPS and INS.
According to ublox documentation it is possible to enable fusion filter for M8N and feed the data to it.
Related
I believed the IMU would get me this information, but I was at first confused as to why it didn't. The IMU will only report live feedback of the device once it is in motion (like any phone would), but it doesn't give me information about its current state.
What I would like to have is a return of the camera's rotation (yaw, pitch, roll) at any given moment so that I could later calibrate my work to it. Is there a way to do this with IMU that I am not seeing?
IMU data begins streaming after calling k4a_device_start_imu(). If you are not seeing a stream then there is likely a bug in your code.
There is some documentation for k4a_device_get_imu_sample() here: https://microsoft.github.io/Azure-Kinect-Sensor-SDK/master/group___functions_ga8e5913b3bb94a453c7143bbd6e399a0e.html#ga8e5913b3bb94a453c7143bbd6e399a0e
I'm trying to rectify GPS readings using Kalman Filter. I already have an IMU with me which has an accelerometer, gyro, and magnetometer.
I've tried looking up on Kalman Filters but it's all math and I can't understand anything. Any example codes would be great!
EDIT: In my project, I'm trying to move from one LAT,LONG GPS co-ordinate to another. I'd like to get smooth GPS reading instead of the ones showing displacement even when there's no movement. I am thinking of using an accelerometer to check displacement and remove GPS reading outliers. However, from what I've read, a Kalman Filter is used for such an application. But every example of it I've found is in some high-level language. It would be great if there's something in C I can build on. Thanks!
You're asking for a code example, without specifying any details, so it's hard to help you further.
You could try browsing github by searching for "kalman", and limit your query to C code.
https://github.com/search?l=C&q=kalman&type=Repositories
Till now I have been able to create an application where the Kinect sensor is at one place. I have used speech recognition EmguCV (open cv) and Aforge.NET to help me process an image, learn and recognize objects. It all works fine but there is always scope for improvement and I am posing some problems: [Ignore the first three I want the answer for the fourth]
The frame rate is horrible. Its like 5 fps even though it should be like 30 fps. (This is WITHOUT all the processing) My application is running fine, it gets color as well as depth frames from the camera and displays it. Still the frame rate is bad. The samples run awesome, around 25 fps. Even though I ran the exact same code from the samples it wont just budge. :-( [There is no need for code, please tell me the possible problems.]
I would like to create a little robot on which the kinect and my laptop will be mounted on. I tried using the Mindstorms Kit but the lowtorque motors dont do the trick. Please tell me how will I achieve this.
How do I supply power on board? I know that the Kinect uses 12 volts for the motor. But it gets that from an AC adapter. [I would not like to cut my cable and replace it with a 12 volt battery]
The biggest question: How in this world will it navigate. I have done A* and flood-fill algorithms. I read this paper like a thousand times and I got nothing. I have the navigation algorithm in my mind but how on earth will it localize itself? [It should not use GPS or any kind of other sensors, just its eyes i.e. the Kinect]
Helping me will be Awesome. I am a newbie so please don't expect me to know everything. I have been up on the internet for 2 weeks with no luck.
Thanks A lot!
Localisation is a tricky task, as it depends on having prior knowledge of the environment in which your robot will be placed (i.e. a map of your house). While algorithms exist for simultaneous localisation and mapping, they tend to be domain-specific and as such not applicable to the general case of placing a robot in an arbitrary location and having it map its environment autonomously.
However, if your robot does have a rough (probabilistic) idea of what its environment looks like, Monte Carlo localisation is a good choice. On a high level, it goes something like:
Firstly, the robot should make a large number of random guesses (called particles) as to where it could possibly be within its known environment.
With each update from the sensor (i.e. after the robot has moved a short distance), it adjusts the probability that each of its random guesses is correct using a statistical model of its current sensor data. This can work especially well if the robot takes 360ยบ sensor measurements, but this is not completely necessary.
This lecture by Andrew Davison at Imperial College London gives a good overview of the mathematics involved. (The rest of the course will most likely be very interesting to you as well, given what you are trying to create). Good luck!
I'm implementing an accelerometer-based pedometer, and I was wondering if there was any known algorithms to handle that.
You have probably found this:
Enhancing the Performance of Pedometers Using a Single Accelerometer
Anyhow, I am also interested in finding a good algorithm, I am curios what other answers you will get. :)
There is an app called Sensor data that you can uses to gather experimental data so you can then analyze it and try to find an algorithm.
Its going to be quite tricky to find a very good algorithm especially for the iPhone since its accelerometer is quite noisy
There's an interesting paper (with source code) here that may be of help: http://www.analog.com/static/imported-files/application_notes/47076299220991AN_900.pdf.
The charts are interesting. If I were to do this myself I would probably sample the data at a fairly high frequency, convert to frequency domain with a FFT, apply a digital band-pass filter to cut off all frequencies outside the expected minimum/maximum walking speeds (including any DC offset), do a reverse-FFT to reconstruct the now-filtered signal and then run the resulting data through an edge-detector with a Hysteresis function. This is all pure speculation of course but looking at those charts I think it would work, it would be relatively fast to code up and well within the processing power of a mobile phone.
I'm looking for the most realistic way of playing sound of a rolling ball. Currently I'm using a Wav sample that I play over and over as long as the ball is moving - which just doesn't feel right.
I've been thinking about completely synthesizing the sound, which I know very little about (almost nothing), I'd be grateful for any tutorials/research materials/samples concerning synthesis of sound of a ball made of particular material rolling on surface made of another material. Also if this idea is completely wrong, please suggest another way of doing this.
Thanks!
I would guess that you'll get the biggest bang for your buck by doing a dynamic frequency adjustment on the sound that makes the playback frequency proportional to the velocity of the ball. I don't know what type of sound library you use, but most will support some variant of this.
For example, in FMOD you could use the Channel::setFrequency method. Ideally, you would compute your desired playback frequency based on your WAV's original sample frequency (Fo), the ball's current velocity (Vc), and the ball's 'ideal' velocity at which the default WAV sounds right (Vi). Something generally like:
F = Fo * ( Vc / Vi )
This will tend to break down as the ball gets farther away from the 'ideal' velocity. You might want to have several different WAVs that are appropriate for different speed ranges that you switch to at certain threshold velocities. Within each WAV's bracket, you'd do the same kind of frequency adjustment.
Another note: this is probably not something that is worth doing every frame. I'd guess that doing this more than 20 times per second would be a waste of time.
ADDENDUM: Playback frequency scaling like this can also be used for simulating the Doppler effect as well. Once you have your adjusted playback frequency, you'd perform another scale of the Frequency based on the velocity of the ball relative to the 'listener' (the camera).
Have you tried playing the sound forward, then playing it backward, and looping that? I use this trick graphically to creating repeating patterns. I don't know much about sound but it might work?
One approach might be to analyze the sound of a rolling ball, and decompose it into its component waveforms. Then you'd be able to generate your own wav file with synthesized waves.
You should be able to do this using an FFT on a sample of the sound.
One drawback is that the sound will likely sound synthesized - you'll have to add noise and such to make it sound more realistic. Getting it to sound real enough may be the hardest part.
I don't think you need the trouble to synthesize that. It would be way too hard to even sound convincing.
Depending on how your scene is, you could loop the sound foward/backwards and simulate a doppler effect applying a low pass filter and/or changing it's pitch.
By the way, freesoung.org is a great place for free samples. They are not professionally recorded but are a good starting point for manipulation. On the other hand, sound ideas has some great sample cds (they're actually industry standard) if you can find them on the cheap. You just have to search for which one has rolling ball sounds.
I really like the approach described in this SIGGRAPH paper:
http://www.cs.ubc.ca/~kvdoel/publications/foleyautomatic.pdf
It describes synthesizing the sound of a rock rolling in a wok (no, really :). The idea is to use modal synthesis (i.e. convolved impulse responses), and the results can be very convincing.
Here's a link to the video demo that goes with the paper:
http://www.cs.ubc.ca/~kvdoel/publications/foleyautomatic.mpeg
And here's a link to the JASS library (written by one of the authors), which was used to create the sound for the video:
http://www.cs.ubc.ca/~kvdoel/jass/jass.html
I'm not sure if you could make it run on a smart phone, but with an efficient enough convolution routine/approximation you might be able to do something interesting...
My question is 'why?' - do you see some benefit in this, or is it just for fun? Your question implies that you aren't happy with the wav you are using but I strongly believe that synthesising your own is going to sound far inferior.
If your wav sample doesn't sound right, I'd suggest try to find another sample. Synthesising a sound is not easy and is never going to sound as realistic as your sample.
Real time synthesis may require more resources for processing and computation. You may very well end up prerendering your synthesised sound into a wav file and performing a playback.
If you want to simulate the sound of different materials then you can use some DSP, or even simple tricks like slowing or speeding the wav playback. The simplest way is the prerender these in another application and store one copy of the file for each use.