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Algorithmic Robotics

Common code for class. Currently many of the packages are from the duckietown/Software github repository or built off of said packages.

Contents

  • ar_tags/
    • src/tag_detector_node.py - publishes AR tag detections (IDs, relative positions)
  • dagu_car/
    • launch/dagu_car.launch - starts the dagu_car nodes and remaps topics
    • script/drive_straight_test.py - run this to test the wheel calibration
    • src/kinematics_node.py - converts car velocities to wheel speeds
    • src/wheels_driver_node.py - sets wheel speeds based on received commands
  • duckietown/
    • config/dagu_car/kinematics/pi.yaml - wheel calibration
    • config/ground_projection/pi.yaml - extrinsic camera calibration
    • config/pi_camera/pi.yaml - intrinsic camera calibration
    • launch/ - launch files that start nodes across multiple packages
  • duckietown_msgs/
    • msg/ - message definitions used across duckietown
  • ground_projection/
    • scripts/test_projection_auto.py - run this to test extrinsic camera calibration
  • intersection_control/
    • config/maneuvers.yaml - open-loop turn descriptions
    • config/map.yaml - graph representation of roads
    • src/stop_line_filter.py - publishes stop-line readings
    • src/supervisor_node.py - manages intersections (and control mode switching)
  • keyboard_control/
    • src/keyboard_control_node.py - publishes car velocities based on key presses
  • lane_control/
    • src/lane_controller_node.py - publishes car velocities based on lane pose estimates
  • lane_filter/
    • src/lane_filter_node.py - publishes lane pose estimates
  • localization/
    • config/landmarks.yaml - AR tag IDs and locations
    • src/localization_node.py - estimates car pose based on AR tags and odometry (lab 10)
  • pi_camera/
    • launch/camera.launch - starts the camera nodes and remaps topics
    • src/cam_info_node.py - publishes camera calibration info each time an image is received
    • src/camera_node.py - publishes compressed camera images

Environment

  • Raspberry Pi 3, Ubuntu Mate 14.04, Python 2.7.12, OpenCV 2.4.9, ROS Kinetic

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