The application is responsible for performing the primary control algorithm
that is supposed to stabilize the quad during flight. It also is responsible
for communicating with the ground station, responding to any commands it
receives and sending logs when appropriate.
## Controller Network (Control algorithm)
First read the [documentation for the computation graph library](src/computation_graph/README.md) to understand how the graph computes functions from a directed graph.
To visualize the default control network, from the quad folder, run `make diagram` with graphviz installed, and an image of the control network will show up as `network.png` in the _src/gen\_diagram_ folder. To see the autonomous controller, you can change the call at the bottom of `control_algorithm_init` from `connect_manual()` to `connect_autonomous()` before running `make diagram`. Just be sure to change it back to `connect_manual()` before the final build. Below is a simplified version of the autonomous controller that shows the control network for autonomous flight using VRPN data. (Unused blocks relating to manual flight and optical flow have been removed, as well as Ts\_IMU and Ts\_VRPN, which are blocks that keep track of the sampling period)
One potential confusing point to take note of is the difference between "(X/Y) Vel PID" and "(X/Y) Vel" blocks. "(X/Y) Vel" is just a PID controller that has Kd=-1, which results in calculating the derivative of position to provide velocity. For clarity, it would be a good idea to create an actual differentiation block.
* Note our use of derivative on value, not error
## Optical Flow
The current (end of may17-16) state of optical flow is that it can be used autonomously be uncommenting all four defines at the top of `control_algorithm.c`. It is relatively stable, but drifts over time. Setpoints do work, but yaw needs fixing (See issue #23).
We are using the PX4Flow optical flow sensor. Read more about it [here](https://pixhawk.org/modules/px4flow) and [here](https://pixhawk.org/dev/px4flow). The source code for the firmware can be found on [Github](https://github.com/PX4/Flow).
### Improvements to be made
* Compensate for rotation of sensor. The PX4Flow has the ability to enable gyroscope compensation (The firmware must be re-flashed for changes to persist), but when we tried it, the output was much worse. We then implemented our own gyroscope correction, using the complementary-filtered pitch and roll, since they will not drift over time (Using raw gyro would result in drift in position because of gyrosope angle drift). The actual data didn't look much worse, and for large, slow movements, the gyroscope compensation seemed to help prevent incorrect measurements, but it always made flight worse, probably beause of high-frequency noise. Using the complementary filter might be the cause, since it essentially high-passes the accelerometer readings, which are very noisy. We then also tried putting a low-pass filter on phi_dot and theta\_dot, but it didn't help flight. Possibly the delay added by the filter caused the correction to not align with the actual movements.
* Possibly just switch to a better optical flow sensor. This one has not had any developments in the past couple years, is hard to buy, and is poorly documented. The best documentation is to actually look in the source code, because we have found multiple discrepancies in the documentation.
