Hello Tapio, thanks for comment and for the advice. I would love to post more often, even as much as four times a week because I have a lot of video ideas just piling up. Unfortunately, this is just a hobby and I can only spare the 10 hours a week or so on it at the moment. I work full time as a control system designer and I use this channel as a way to relate some of the things we learn in school to real engineering. Maybe one day I can turn this into a full time gig.
Brian, your videos are the best. I see you're not making as many as you once were. I understand how time consuming they are to create. Just wanted to express my respect for your command of the subject and the time you took to make it understandable for an old flight software guy. Highest praise.
You should post more frequently. I like your style very much. You keep it simple and clear. I watch your videos to "refresh my basics". Someday I would like to see a basic introduction to Kalman Filter. Another video blog I enjoy is the EEVblog. Dave Jones started that slow and is now doing it full time. But you have to post at least twice a week.
People might be wondering what the FIFO is for because a lot of uses in robotics need as recent as possible data. In cameras (including phones), the gyroscope sensor records the movement and can remove some of the motion blur from the image. In this application, the MCU just goes fetching the trajectory in the mems buffer after being done with the picture issue. Cameras and phones are big business in the mems industry, so they get features.
Hello Brian, First of all, I like to thank you for the insight you provided. I have recently started working with sensors. I am finding it bit challenging to understand thoroughly. Can you recommend me any book or study material that I should refer? I also like to ask if you can make some tutorial over spacecraft attitude determination and control? I am truly grateful for the effort you put to make this video. It has been a great help for me so far. Thanks, Hrithik
Hi Brian -- I'm dealing with a problem relevant to what you cover starting at 4:30. I'm using the vl6180x optical sensor's ranging functionality in interrupt mode in order to "wake up" the processor if the range reading drops below a certain threshold. I'm effectively using the vl6180x as a binary proximity sensor with a variable threshold. Now, I'm running into a problem in setting the sampling rate. According to the datasheet (p. 26), each range measurement is composed of a pre-cal period, a convergence period, and an averaging period. The pre-cal period is static, but the max convergence and averaging period are tunable. What's unclear to me is exactly what's being averaged if only one measurement has been taken during the complete sequence (pre-cal _> converge -> average). I.e. if each convergence period yields *one* range measurement the sensor has converged upon, then no averaging can take place. This makes me think the true measurement flow is as follows: pre-cal -> averaging period containing N convergence periods. The number of measurements averaged, N, depends on the convergence time, which is dependent on the application conditions. Another possibility is that pre-cal periods are necessary for each convergence measurement, i.e. total measurement time = averaging period time = N*(pre-cal time + convergence time), but the pre-cal time is set to 3.2 ms, so averaging even 5 measurements would require >15 ms, which seems unrealistically slow. Can you shed some light on this problem? Is the averaging period simply buffering the raw measurements read during this period?
Nice video as always. If you have time in the future, can you talk about how the electrical characteristics drive your designs and how to design one? Thanks!
Hi, from watching your videos I've learned a whole lot, but as I see papers that other people write abour IMUs, etc, they analyze noise using PSD, but a lot of these PSD plots have different units, do you know of a paper that explain those, or please make avideo explaining them when you get a chance.. :) thanks
This is something that they don't teach in college. You get exposed to spec. sheets in labs, but they are often misinterpreted :P "Oh, 6.1 mA supply current? Better find a 6 mA battery!" lol
Hello Tapio, thanks for comment and for the advice. I would love to post more often, even as much as four times a week because I have a lot of video ideas just piling up. Unfortunately, this is just a hobby and I can only spare the 10 hours a week or so on it at the moment. I work full time as a control system designer and I use this channel as a way to relate some of the things we learn in school to real engineering. Maybe one day I can turn this into a full time gig.
After full of 11 years, thank you again
Brian, your videos are the best. I see you're not making as many as you once were. I understand how time consuming they are to create. Just wanted to express my respect for your command of the subject and the time you took to make it understandable for an old flight software guy. Highest praise.
Great video, no muddying up the water just enough info to inspire trying it for myself. Keep them coming!
You should post more frequently. I like your style very much. You keep it simple and clear. I watch your videos to "refresh my basics". Someday I would like to see a basic introduction to Kalman Filter. Another video blog I enjoy is the EEVblog. Dave Jones started that slow and is now doing it full time. But you have to post at least twice a week.
People might be wondering what the FIFO is for because a lot of uses in robotics need as recent as possible data. In cameras (including phones), the gyroscope sensor records the movement and can remove some of the motion blur from the image. In this application, the MCU just goes fetching the trajectory in the mems buffer after being done with the picture issue. Cameras and phones are big business in the mems industry, so they get features.
Thank you Brian, very helpful guide. Truly grateful for the effort you put to make this video. It has been a great help.
You are amazing Brian Douglas! Thanks a lot!
Hello Brian,
First of all, I like to thank you for the insight you provided.
I have recently started working with sensors. I am finding it bit challenging to understand thoroughly. Can you recommend me any book or study material that I should refer? I also like to ask if you can make some tutorial over spacecraft attitude determination and control?
I am truly grateful for the effort you put to make this video. It has been a great help for me so far.
Thanks,
Hrithik
Hi Brian -- I'm dealing with a problem relevant to what you cover starting at 4:30. I'm using the vl6180x optical sensor's ranging functionality in interrupt mode in order to "wake up" the processor if the range reading drops below a certain threshold. I'm effectively using the vl6180x as a binary proximity sensor with a variable threshold. Now, I'm running into a problem in setting the sampling rate. According to the datasheet (p. 26), each range measurement is composed of a pre-cal period, a convergence period, and an averaging period. The pre-cal period is static, but the max convergence and averaging period are tunable. What's unclear to me is exactly what's being averaged if only one measurement has been taken during the complete sequence (pre-cal _> converge -> average). I.e. if each convergence period yields *one* range measurement the sensor has converged upon, then no averaging can take place. This makes me think the true measurement flow is as follows: pre-cal -> averaging period containing N convergence periods. The number of measurements averaged, N, depends on the convergence time, which is dependent on the application conditions. Another possibility is that pre-cal periods are necessary for each convergence measurement, i.e. total measurement time = averaging period time = N*(pre-cal time + convergence time), but the pre-cal time is set to 3.2 ms, so averaging even 5 measurements would require >15 ms, which seems unrealistically slow. Can you shed some light on this problem? Is the averaging period simply buffering the raw measurements read during this period?
Incredible videos, What do you use for your video explanations?? Is it some sort of digital notepad?
Thanks,
Nice video as always. If you have time in the future, can you talk about how the electrical characteristics drive your designs and how to design one? Thanks!
what a video
hats off sir
keep going like this
Great job thanks. Will you do it for GPS and pressure sensor too?
I still don't know what is the difference of gyroscope, accelerometer and compass. And where each one is used.
Hi,
from watching your videos I've learned a whole lot, but as I see papers that other people write abour IMUs, etc, they analyze noise using PSD, but a lot of these PSD plots have different units, do you know of a paper that explain those, or please make avideo explaining them when you get a chance.. :) thanks
This is something that they don't teach in college. You get exposed to spec. sheets in labs, but they are often misinterpreted :P "Oh, 6.1 mA supply current? Better find a 6 mA battery!" lol
hey. thanks a lot man. you are amazing!!!!
thank you
Found a video where you explain it. :P
I love you