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However, because this application dealt with an embedded microprocessor, I considered two atan implementations from [4]: | However, because this application dealt with an embedded microprocessor, I considered two atan implementations from [4]: | ||
− | *'closed form' (finite number of terms) approximation, whose range is inherently bounded to | + | *'closed form' (finite number of terms) approximation, whose range is inherently bounded to [-45 ''degrees'',+45 ''degrees'']. |
<math>arctan(x) \approx \frac{x}{1 + .28125x^{2}} , -1 \leq x \leq 1</math> | <math>arctan(x) \approx \frac{x}{1 + .28125x^{2}} , -1 \leq x \leq 1</math> | ||
− | *lookup table (LUT) (w/ or w/o interpolation) | + | *lookup table (LUT) (w/ or w/o interpolation), in which the ''arctan'' argument is used as an index to the LUT. |
+ | |||
+ | Because the neither accuracy nor range of sensitivity was critical for my application, I implemented a 256-value LUT in which each ''arctan'' argument was multiplied by 255, which means ''arctan_LUT[255] = 45 degrees''. In other words, all ''arctan'' arguments were normalized and bounded to '1'. However, the LUT could easily be extended up to ''90 degrees'' in both directions. | ||
+ | |||
+ | Also, I utilized the property that: | ||
+ | <math>arctan(-x) = -arctan(x)</math> | ||
+ | in order to effectively double the table size by only feeding in positive table indices, but appending a negative sign to the table value if appropriate. When dealing with a fixed-point microprocessor like the HCS12, little tricks like this can significantly reduce the number of cycle necessary to calculate a value. | ||
Details of an LUT implementation (w/o interpolation) can be seen in the following graphs: | Details of an LUT implementation (w/o interpolation) can be seen in the following graphs: |
Revision as of 13:10, 12 November 2012
Determining Orientation from Accelerometer (alec green)
OUTLINE . introduction . continuous equations (..to be completed..) . discretization (..to be completed..) . references
Introduction
An accelerometer is useful for measuring orientation relative to Earth's surface ground ('static acceleration' due to gravitational force) or accelerating motion throughout space ('dynamic acceleration' due to non-gravitational force such as a car speeding up or a human shaking an accelerometer-clad device). However, note that accelerometers are implicity restricted to measuring acceleration, and cannot measure velocity. For example, constant nonzero velocity will produce same measurement as zero velocity.
It's important to first determine if an accelerometer is appropriate for your application. If you're not sure, you may consider other orientation/position sensing devices such as: gyroscope (angular velocity), magnetic compass (2D direction of maximum local magnetic field), magnetometer (magnitude and 3D direction of local magnetic field), GPS (rough 3D position).
In order to achieve higher-level measurements such as 'dead reckoning' (calculation of position and orientation in 3D space), you will need to combine sensor readings. For example, an accelerometer, gyroscope, and magnetometer are commonly packaged together as an 'intertial measurement unit' (or IMU) to be used by 'quadcopter' hobbyists. This 'sensor fusion' also allows for sensors to recalibrate each other such that measurement 'drift' of certain sensors (esp. gyroscope) is minimized. This inter-recalibration can further benefit from probabilistic noise-reducing filters such as the Bayesian or Kalman filter.
The following video may give you a better idea of what an accelerometer can be used for. Extensive description provided at YouTube page (access by clicking on YouTube logo in lower right-hand side of video).
Continuous Equations
It's instructive to read through pages 3-4 of [2] in order to understand how an accelerometer works on a physical level, but not necessary to interpret the analog or digital signals generated from the sensor.
Discretization
Because an HCS12 microcontroller works with fixed-point integers, computing the required arctangent (and sqrt equations is non-trivial. The atan function you might normally invoke from the <math.h> library requires floating point numbers. An example implementation can be seen here [4].
However, because this application dealt with an embedded microprocessor, I considered two atan implementations from [4]:
- 'closed form' (finite number of terms) approximation, whose range is inherently bounded to [-45 degrees,+45 degrees].
$ arctan(x) \approx \frac{x}{1 + .28125x^{2}} , -1 \leq x \leq 1 $
- lookup table (LUT) (w/ or w/o interpolation), in which the arctan argument is used as an index to the LUT.
Because the neither accuracy nor range of sensitivity was critical for my application, I implemented a 256-value LUT in which each arctan argument was multiplied by 255, which means arctan_LUT[255] = 45 degrees. In other words, all arctan arguments were normalized and bounded to '1'. However, the LUT could easily be extended up to 90 degrees in both directions.
Also, I utilized the property that: $ arctan(-x) = -arctan(x) $ in order to effectively double the table size by only feeding in positive table indices, but appending a negative sign to the table value if appropriate. When dealing with a fixed-point microprocessor like the HCS12, little tricks like this can significantly reduce the number of cycle necessary to calculate a value.
Details of an LUT implementation (w/o interpolation) can be seen in the following graphs:
A finished implementation (with atan LUT), displaying analog axis outputs and calculated orientation angles (roll, pitch) can be seen here. As before, an explanation of the video can be found on the original Youtube page.
References
[1] Freescale Semiconductor, "±1.5g, ±6g Three Axis Low-g Micromachined Accelerometer" Freescale Datasheet. <http://www.sparkfun.com/datasheets/Components/General/MMA7361L.pdf>
[2] L. Salhuana, "Tilt Sensing Using Linear Accelerometers," Freescale Application Note. <http://www.freescale.com/files/sensors/doc/app_note/AN3461.pdf>
[3] "atan.c," Apple Open Source. <http://opensource.apple.com/source/Libm/Libm-315/Source/Intel/atan.c>
[4] A. Ukil et al., "Fast Computation of arctangent Functions for Embedded Applications: A Comparative Analysis," IEEE ISIE 2011. <http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5984330>
[5] N. Jones, "A tutorial on lookup tables in C", EmbeddedGurus.com. <http://embeddedgurus.com/stack-overflow/2010/01/a-tutorial-on-lookup-tables-in-c/>
[6] "Fast square root in C," IAR Application Note. <http://netstorage.iar.com/SuppDB/Public/SUPPORT/000419/AN-G-002.pdf>