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| from flight_environment import FlightEnvironment | |
| from planners.path_planner import rrt_planner | |
| from planners.trajectory_generator import plan_trajectory_through_path, plot_trajectory | |
| from plot_plotly import plot_cylinders | |
| env = FlightEnvironment(50) | |
| start = (1,2,0) | |
| goal = (18,18,3) | |
| # --------------------------------------------------------------------------------------------------- # | |
| # Call your path planning algorithm here. | |
| # The planner should return a collision-free path and store it in the variable `path`. | |
| # `path` must be an N×3 numpy array, where: | |
| # - column 1 contains the x-coordinates of all path points | |
| # - column 2 contains the y-coordinates of all path points | |
| # - column 3 contains the z-coordinates of all path points | |
| # This `path` array will be provided to the `env` object for visualization. | |
| #path = [[0,0,0],[1,1,1],[2,2,2],[3,3,3]] | |
| path = rrt_planner(env, start, goal, step_size=1) | |
| # --------------------------------------------------------------------------------------------------- # | |
| # 3D env plot, choose one - Plotly or Matplotlib - comment the other | |
| # Plotly | |
| plot_cylinders(env, path) | |
| # Matplotlib (laggy) | |
| #env.plot_cylinders(path) | |
| # --------------------------------------------------------------------------------------------------- # | |
| # Call your trajectory planning algorithm here. The algorithm should | |
| # generate a smooth trajectory that passes through all the previously | |
| # planned path points. | |
| # | |
| # After generating the trajectory, plot it in a new figure. | |
| # The figure should contain three subplots showing the time histories of | |
| # x, y, and z respectively, where the horizontal axis represents time (in seconds). | |
| # | |
| # Additionally, you must also plot the previously planned discrete path | |
| # points on the same figure to clearly show how the continuous trajectory | |
| # follows these path points. | |
| t_traj, traj = plan_trajectory_through_path(path, desired_speed=1.0, samples_per_meter=8) | |
| plot_trajectory(t_traj, traj, path) | |
| # --------------------------------------------------------------------------------------------------- # | |
| # You must manage this entire project using Git. | |
| # When submitting your assignment, upload the project to a code-hosting platform | |
| # such as GitHub or GitLab. The repository must be accessible and directly cloneable. | |
| # | |
| # After cloning, running `python3 main.py` in the project root directory | |
| # should successfully execute your program and display: | |
| # 1) the 3D path visualization, and | |
| # 2) the trajectory plot. | |
| # | |
| # You must also include the link to your GitHub/GitLab repository in your written report. | |