Performance & calibration

Embedded MotionApps 2.0 as well as Motion Driver use the Digital Motion Processor (DMP™) located on the sensor device to perform 6-axis MotionFusion. The Embedded MotionApps Platform MotionFusion reads sensor fusion results from the DMP using the FIFO buffer.
For 9-axis operation in the MotionFit SDK the micro is required to integrate compass data as well as some calibration routines.

You can see the terms LSB/dps and LSB/g relatively in our datasheet Gyroscope Specifications and Accelerometer Specifications sections. You need to look at your Full-Scale Range setting for accelerometer and gyroscope, then find the corresponding sensitivity scale factor values from table. Those sensitivity scale factors used for converting from LSB to dps (degrees per second) and g units.

When your accelerometer full-scale range is set to ±2g, you will read 16384 LSB as 1g from the accelerometer output, hence you can make your conversions based on that. When your gyroscope full-scale range is set to ±250 dps, every 131 LSB will equate to 1dps.

I2C slave addresses can be 0x68 or 0x69 and can be configured by the logic level of the pin AP_AD0.

9 axis MotionTracking® combines gyroscope, accelerometer, and TMR magnetometer sensor data. The resulting angular frame is relative to both gravity (down) and north.

The advantages of 9 axis MotionTracking® over 6 axis MotionTracking® are that 9 axis MotionTracking® results are usable for navigation and other applications which require information about the angle relative to north. It also eliminates any heading drift which may be present in a 6 axis MotionTracking® solution so that users are pointed in the correct direction without delay due to recalibration.

Both accelerometers and magnetometers are noisy sensors, which means they exhibit a slow response rate (due to noisy filtering) in fast moving systems. Accelerometer measurements are also affected by motion. By using a gyroscope and sensor fusion, the sensor fusion solution will have a faster response rate and track small, quick movements much more quickly. Gyroscope sensor fusion also makes it possible to sense linear acceleration separately from gravity.

Euler angles are a representation of an angular frame, as are quaternions and rotation matrices.

Euler angles are a set of three angles, corresponding to pitch, roll, and yaw. Euler angles may be constructed according to many conventions. The axes of and ordering of ordering of pitch, roll, and yaw vary by convention.

Euler angles are not commutative. For any Euler angles A, B, a rotation A followed by B is not

(B + A) is necessarily equal a rotation B followed by A (B + A). Because of this algebraic property, Euler angles are often not very useful for signal processing applications.

Euler angles suffer from a pair of singularity points at which only two of the three angles are significant. The derivative of the Euler angles is discontinuous at this point. This condition is often called gimbal lock.

A quaternion is a number with a real and three imaginary components, q = a + i b + j c + k d

A quaternion represents a rotational frame in a form related to the angle theta and axis v of rotation, where v is a three-dimensional unit (length 1) vector, and q = sin (theta / 2) + i * vx * cos(theta/2) + i * vy * cos(theta/2) + k * vz * cos(theta/2)

You can easily convert a quaternion to Euler angles or a rotation matrix.

http://en.wikipedia.org/wiki/Quaternions_and_spatial_rotation

The DMP calculates the MotionFusion solution as a quaternion because it is the most efficient representation for mathematical applications.

An angular frame is a representation of an object’s orientation in 3D space. It is commonly described using Euler angles or a quaternion. Please see http://en.wikipedia.org/wiki/Euler_angles and http://en.wikipedia.org/wiki/Quaternions_and_spatial_rotation

An angular frame does not describe the 3D location of an object, only its rotation relative to a reference. The reference rotation for a 6-axis angular frame is flat and level—that is, the vertical axis of the object is aligned with up/down. The reference rotation for a 9-axis angular frame is flat, level, and north: the vertical axis of the object is aligned up/down, and the forward axis of the object is aligned north/south.

The algorithms for sensor fusion are TDK-InvenSense IP and runs in encrypted form on the DMP or as a binary on the host. Sensor fusion outputs quaternions, which is a 3D representation of the movement of an object in space. As long as the application is using quaternions, there is no need for the system developer to get burdened with the details of sensor fusion implementation

The Embedded Workbench Platform is designed to optimize system resource usage efficiently. Here's what you need to know:

1. Resource Management: The platform uses intelligent resource allocation to distribute the load evenly across your system. It monitors CPU, memory, and I/O usage in real-time to prevent bottlenecks.

2. Adaptive Performance: The workbench automatically adjusts its resource consumption based on your system's current state. During periods of high activity in other applications, it scales back to maintain system stability.

3. Configuration Options: You can customize resource limits through the Settings panel. Navigate to Preferences > Performance to set maximum CPU and memory usage thresholds.

4. Background Processing: Most intensive operations are performed asynchronously in the background, ensuring your main workflow remains responsive.

5. Best Practices:
  • Close unnecessary projects when not in use
  • Enable auto-save to reduce write operations
  • Use the built-in profiler to identify resource-heavy operations
  • Keep your platform updated for the latest optimizations

If you're experiencing unusual resource usage, try running the diagnostic tool (Tools > System Diagnostics) to identify potential issues.