Repository for generating UAM trajectories and write them to output CSV files.
This code was developed on Julia1.1.
Ensure that the following packages are installed in your current version of Julia: Distributions, Convex, ECOS, DataFrames, CSV.To install any of these packages that have not yet been installed, simply run:
include("setup.jl")The following lines will generate a trajectory file titled "test.csv" with data for a nominal landing trajectory.
include("UAMTrajectoryGenerator.jl")
τ = nominal_landing()
generate_trajectory_file(τ, "test.csv")If no trajectory type is specified, a random trajectory type will be chosen and generated (uniform among all possible types):
generate_trajectory_file("test.csv")If you want to generate more than 1 trajectory per file, you can add this as the last required argument. The following line will generate a file called "test.csv" with 3 trajectories.
generate_trajectory_file("test.csv", 3)The first column of the resulting CSV file will be the time in seconds and the following three columns will be the x-, y-, and z-position respectively in feet. To test on your system, include the RUN_UAM.jl script. It should generate a file in the output directory that matches the "uam_traj_ex.csv" file in the examples directory.
SAMPLER - abstract type of which specific trajectory samplers are subtypes. A sampler contains the distributions of random variables associated with a particular trajectory type (e.g. initial altitude, glideslope, etc.)
UAM_TRAJECTORY - abstract type of which specific trajectory types such as NOMINAL_LANDING and VERTICAL_ASCENT are subtypes. All trajectory types contain a corresponding sampler, a time step, acceleration constraints, position, velocity, and a place to store each variable in the sampler.
TRAJECTORY - contains position (p), velocity (v), and acceleration (a) for an entire trajectory. Each row is the x, y, and z values of the variable at a particular time step with time increasing with the rows.
sample_features!(τ::UAM_TRAJECTORY) - replaces feature values in the trajectory by sampling new values according to the distributions specified in the sampler.
generate_trajectory!(τ::UAM_TRAJECTORY) - runs sample_features!(τ) on the trajectory and uses the sampled features to generate the trajectory by solving a constrained convex optimization problem. When the solve_trajectory!(τ::UAM_TRAJECTORY) function is called, the position p and velocity v in the trajectory object will be replaced with the values for the newly generated trajectory.
If you want to hold any features constant during the trajectory, you will need to add a line after sample_features!(τ) gets called. For example, if you know you want a nominal landing with an starting altitude of 500 ft, using the following lines of code to generate the trajectory:
τ = nominal_landing()
sample_features!(τ)
τ.z_init = 500
solve_trajectory!(τ)setup.jl - file that installs required packages that you do not currently have
UAMTrajectoryGenerator.jl - Main file to include for UAM trajectory generation that sets up constants and types; includes all necessary files, and defines general functions for all types of trajectories.
HighReconaissance.jl - defines functions and types for high reconaissance trajectories.
Nominal Landing.jl - defines optimization problem and types for nominal landing trajectories.
NominalTakeoff.jl - defines optimization problem and types for nominal takeoff trajectories.
VerticalAscent.jl - defines optimization problem and types for vertical ascent takeoff trajectories.
VerticalDescent.jl - defines optimization problem and types for vertical descent landing trajectories.
run_uam.jl - sample script for generating uam trajectory files
sample_uam_traj.csv - sample model output for one uam trajectory