The provided scripts are named based on their function and includes a simulation (sim.py) for the dynamics (dynamics.py) of a octorotor (robot.py), facilitated by controllers (control.py) and a planner (planner.py). The simulation is run via main.py by running python main.py from the root of this repository. The simulation will produce three plots: 1) 3D position, 2) position tracking and 3) attitude (i.e. roll, pitch and yaw) of the octorotor.

The provided scripts were developed using Python 3.8.10.

See dynamics.py for the Euler Lagrange formulation of the octorotors dynamics

See the included derivation of my control allocation matrix in control_allocation_matrix.jpg.

See the suggestion for the inverse of my control allocation matrix in control_allocation_matrix.jpg. Alternatively, in the "px4_generate_mixer" directory I've included a script to produce the desired "mixer" matrix. From the root of the "px4_generate_mixer directory", simply run python px_generate_mixers.py -f octa_plus.toml --sixdof in terminal.

See the computeReferenceAttitude() (line 70) function in the control.py script for the second order attitude reference dynamics.

See the control.py script for the translational and attitude controller (I chose to design a cascade control architecture that takes translational commands and decomposes a desired thrust vector into its respective attitude commands. A low-level attitude controller then controls to the attitude commands.

See sim.py for the gains of each controller.

As mentioned earlier in Task 5, I designed a high-level translational controller. As such, my simulation is characterized by three phases of 5, 10 and 15 second durations, each with associated desired positions. A smooth polynomial is followed to traverse from initial position to goal position. See sim.py for details on the simulation parameters.

Not attempted

Not attempted

Thank you for spending time with my scripts and I look forward to chatting with you through my solutions!