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LIDAR based Obstacle Avoidance with Reinforcement Learning

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LIDAR based Obstacle Avoidance with Reinforcement Learning

This project lists all of the deliverables for the TUM project course Applied Reinforcement Learning (Summer Semester 2019).

Results

Reward Graphs:

State Representation Linear Value Function Approximation Algorithms
State Representation Linear Value Function Approximation Algorithms

More graphs.

Project Demo.:

Simulation Real Turtlebot
Simulation Real Turtlebot

Supplementary Material:

Requirements

Instructions

  1. Move the rl_tb_lidar and stage_ros_u folders to catkin_ws/src directory.
  2. run catkin_make in the catkin_ws directory.
  3. Run source devel/setup.bash command in the catkin_ws directory.
  4. Run roslaunch rl_tb_lidar tb_stage_m1.launch to launch only stage.
  5. Open an another terminal, go to the directory of the python script e.g. cd ~/catkin_ws/src/rl_tb_lidar/src and run python main.py configs/config.yaml.
  6. To try different configurations, edit the configs/config.yaml file accordingly.

Versioning

We version the project with each new deliverable. For the versions available, see the tags on this repository.

Authors

See also the list of contributors.

Acknowledgements

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LIDAR based Obstacle Avoidance with Reinforcement Learning

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