Fully implementation of a path planning pipeline in a dynamic environment. Global path planning, local path planning, and obstacle avoidance for navigating a spacecraft to a goal region while avoiding static and dynamic asteroids.
Project rated with full marks.
Control a spacecraft to safely reach the goal region, moving through an environment full of static and dynamic obstacles.
The spacecraft has a left and a right thruster at the back that can be activated to move forward or backward.
The simulator provides observations about the state of the spacecraft and of the moving obstacles which correspond to the real state of the simulation.
Optimize the distance traveled, the final time, and the actuation effort.
Further info: Assignment.md or this web page.
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To complete the task, at the beginning of the simulation an Informed RRT* algorithm is applied to the static environment only, to obtain the global path the spacecraft has to follow to reach the goal region, given a safe margin from obstacles. The global path found is then smoothed.
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A MPC is exploited to calculate an optimal local trajectory to track the smoothed global path while avoiding the dynamic obstacles. The inputs of the n-steps horizon MPC are the pose and velocity of the spacecraft, the next n points of the smoothed path, and the next n future positions of the dynamic obstacles (predicted through their current pose/velocity and dynamics). The spacecraft is constrained to remain inside the environment boundaries, and to not exceed the speed of 50 km/h.
Video examples:
| Example 1 | Example 2 | Example 3 |
|---|---|---|
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example-1.mp4 |
example-2.mp4 |
example-3.mp4 |
The pipeline and the simulation run within a Docker container on Ubuntu.
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The general simulation settings, like the size of the environment, the number, size and position of the static obstacles, the initial pose/velocity of the spacecraft, and the position of the goal region can be modified in src/pdm4ar/exercises_def/final21/scenario.py.
The number, size and initial pose/velocity of the dynamic obstacles can be modified in src/pdm4ar/exercises_def/final21/sim_context.py. -
The source code of the pipeline is inside the folder src/pdm4ar/exercises/final21.
Run the pipeline and the simulation from the root directory with the command:
make run-final21The image of the Informed RRT* path is saved in src/pdm4ar. The video of the whole simulation is saved inside the generated folder out-docker/final21 as a html page.