Inertial navigation systems

[ahecht]

Originally Posted by Greg Needel

yaw rate sensors are also called gyros they can measure the degree of lean in a direction. think of them as a virtual cup of coffie the coffie stays level to the ground but the cup changes.

Not quite. The yaw rate sensor doesn't measure degree of lean, it measures how fast you are leaning. Imagine if someone put a spedometer on the surface of the coffee that measured the speed between that surface and the mug.

The name Yaw Rate sensor come from the naming conventions for the 6 degrees of motion, heave (sliding up and down), surge (sliding forward and backward), sway (sliding side to side), roll (rotating side to side), pitch (rotating forward and backward) and yaw (rotating side to side). Since yaw referrs to side to side turning, so a Yaw Rate sensor measures the rate of side to side turning.

[Joe Johnson]

Originally Posted by shsdragon

wut are yaw switches

A Yaw Rate Sensor is an angular rate sensor -- it returns a voltage propotional to the rate of rotation of the sensor.

They are pricey ($100 for one from Analog Devices -- ADXRS150 -- mounted on an evaluation PCB -- the chip has a ball grid array interface which is not that easy to use for most teams), but they can be very useful.

Joe J.

[ahecht]

I'd definately agree that the accelerometers were the weak link in the INS system. We didn't get much more than 10 or 15 seconds of good postition data from them, and it took under an hour for the INS to report a velocity greater than the speed of light while sitting on a table. The gyros (which were not kit gyros, as the 75 degree/sec limit of those wasn't enough for us), however, were much more accurate, and should make a return on this year's robot.

Commercial INS systems, which are accurate over a time period of hours, can cost tens of thousands of dollars, and for good reason.

[velocipenguin]

It seems to me that much of the noise inherent to analog accelerometers could be minimized through clever use of shielding and filtering. Team 190's inertial navigation system, while quite impressive, does not appear to be particularly well shielded; the top of that housing appears to be made of Lexan or similar material, which does not provide any electromagnetic shielding. Manufacturers of analog accelerometers usually suggest leaving most of the extraneous copper unetched and grounded on whatever PCB is used, which provides a nice big ground plane surrounding the sensor and its board traces. Performing all of the integration in software would also help somewhat, as op-amp integrators are alarmingly sensitive to noise. Using a simple approximation, such as that suggested elsewhere in this thread, reduces the sample rate enough to filter out quite a bit of the high-frequency noise without compromising the accuracy of the position data. Low-pass filters should be placed on all accelerometer outputs to reduce ripple from the accelerometer's internal clock. Finally, it would be wise to make sure the power supply is VERY well filtered. By paying careful attention to reducing or eliminating noise from external sources, it should be possible to construct an inertial navigation system that is suitably free from error to provide accurate position information throughout the entire match.

[Scooter]

I have been working on a 3 axis accelrometer for a satelltie with the University of Texas, and I can offer a few tips for those that are looking to develop one:

- I reccomend doing it as a seperate circuit and then feeding it into the UART of the robot controller as a digital stream. That way you can get accurate timing, etc.

-Make absolutely sure that you filter the analog vcc line on your microcontroller (an inductor up to power and a cap down to ground), as it needs an extremely accurate 2.5v to take a comparison reading from, and if the line is noisy, it'll throw off your readings.

-Use 2 sets of acclerometers and take the average of the both of them. Thus any error is reduced significantly.

-Search the web for analog smoothing algortihms. There are some really good ones out there.

-Shielding the lines, etc can be helpful, but the biggest difference that I have seen is fildering the analog vcc line. After I did that, my system's accuracy jumped up quite alot.

-There is a good white paper on this site on using the noise from the system to gain additional resolution. It has some good tips...

More later...
Bill

[velocipenguin]

Originally Posted by Scooter

-Make absolutely sure that you filter the analog vcc line on your microcontroller (an inductor up to power and a cap down to ground), as it needs an extremely accurate 2.5v to take a comparison reading from, and if the line is noisy, it'll throw off your readings.

I suspect the circuit inside the robot controller that supplies the analog output Vcc pins and ADC reference pins is already well-filtered and supplied from a stable internal voltage reference. Failing to do this within the robot controller would be a tremendous oversight on IFI's part.

[Scooter]

Originally Posted by velocipenguin

I suspect the circuit inside the robot controller that supplies the analog output Vcc pins and ADC reference pins is already well-filtered and supplied from a stable internal voltage reference. Failing to do this within the robot controller would be a tremendous oversight on IFI's part.

Agreed, and I would be shocked if it wasn't. I was stating that you should filter it if you were building a seperate board with it's own microprocessor to take the readings and the pass them on digitally to the robot controller.

Bill