AA274A: Final Project

See docs/AA274A Final Project Presentation.pdf for a description of the project implementation.

File Descriptions:

Gazebo Simulation Files:

world/signs.world: Defines 3D model stop sign testing environment.

world/project_city.world: Defines 3D model of rough, tentative representation of the final project environment.

world/maze.world: Defines 3D model of the maze world. For HW4.

world/arena.world: Defines 3D model of the arena world. For HW4.

Turtlebot Files:

Launch Files:

launch/asl_turtlebot_core.launch: Launches the core elements of the turtlebot stack (turtlebot drivers, camera, lidar, gmapping, static tf transforms). This should run onboard the jetson.

launch/root.launch: The main configurable launch file on top of which the remaining launch files are built. Can be launched with a simulator or on top of the running hardware turtlebot.

launch/project/project.launch: Launches gazebo with a (rough, tentative) model of the final project environment, as well as the core SLAM and detector nodes. You'll need to run your navigator and other project nodes separately.

launch/section4_demo.launch: used for section 4, testing pose navigation, virtual

launch/homeworks/hw3.launch: launches the world for HW3.

launch/homeworks/hw4_arena.launch: launches the world for ekf_slam.

launch/homeworks/hw4_maze.launch: launches the world for localization.py.

Scripts/Nodes:

scripts/camera_relay.py: Due to networking limitations, your remote machine cannot access messages directly from the raspberry pi. This node forwards images from the raspberry pi via the jetson to the remote machine.

scripts/goal_commander.py: Translates Rviz nav goal clicks (/move_simple_base/goal) to the /cmd_nav topic.

scripts/detector.py: Gazebo stop sign detector from HW2. Publishes to /detector/* where * is the detected object label.

scripts/detector_mobilenet.py: Runs tensorflow mobilenet model for image classification. Publishes to /detector/* where * is the detected object label. DISCLAIMER: The distance estimation is not always very accurate and is noisy. It subscribes to the /scan which takes the closest point (in xy-distance) from any laserscan ring below the horizontal ring, ignoring all points a threshold z_min below the velodyne as ground points. For the current configuration of the Turtlebot, we have set z_min = 16cm. You can combine the camera and/or point cloud to improve the estimate of the distance.

scripts/detector_viz.py: Visualizes camera feed, bounding boxes and confidence for detected objects.

scripts/utils/grids.py: Used for motion planning. Performs collision checking on occupancy grids. grids.py functions/classes are used by scripts/navigator.py.

scripts/navigator.py: Node that manages point to point robot navigation, uses RRT* implementation in an MPC framework along with cubic spline interpolation and the differential flatness controller (from HW1), switching to the pose controller from HW1 when close to the goal.

scripts/utils/utils.py: Utility functions. Currently contains a wrapToPi function, but feel free to add to this.

Rviz Configurations:

Cfg Files:

navigator.cfg: python script to generate dynamic parameter reconfigure for navigator

cfg/gripper_control.yaml: multiple variable configuration for the gripper

Files From HW:

scripts/controllers/ should contain P1_pose_stabilization.py and P2_trajectory_tracking.py from HW1

scripts/planners/ should contain P1_astar.py from HW2

scripts/ should contain the folder HW4 from HW4`

Message Definitions:

msg/DetectedObject.msg: Custom message type that describes detected objects. Contains the following fields:

uint32 id - Label identifying number

string name - Name of identified object

float64 confidence - Classification probability

float64 distance - Distance to object (DISCLAIMER: current implementation relies on /scan topic for distance (see detector.py and detector_mobilenet.py). The distance estimation for works in gazebo for stop signs (HW2) but not tested on hardware)

float64 thetaleft - Left bounding ray of object.

float64 thetaright - Right bounding ray of object.

float64[] corners - Corners of bounding box around detected object with respect to the tf camera frame.

msg/DetectedObjectList.msg`: Custom message type consisting of a list/array of DetectedObject objects and their names. Contains the following fields:

string[] objects - Array of strings corresponding to object names.

DetectedObject[] ob_msgs - Array of DetectedObject objects.

Tensorflow Models:

The .pb files in the tfmodels folder are "frozen" neural network models, and contain both the structure and the weights of pretrained networks. ssd_mobilenet_v1_coco.pb is a pretrained MobileNet v1 model, while stop_sign_gazebo.pb is a model fine-tuend to detect stop signs in Gazebo. We recommend using ssd_resnet_50_fpn.pb, which is a larger, more accurate and robust model, but does not fit on a GitHub repo and can be downloaded here.

The coco_labels.txt file just contains the mapping from the class number output by the model to human-interpretable labels.

There are many other pretrained models you could use, see the Tensorflow detection model zoo for more.

Others:

env_pi.sh: Script to remote launch nodes on the raspberry pi from the jetson. This overcomes the need to ssh into the raspberry pi separately from the jetson to launch the camera node. This goes in ~/catkin_ws/devel/ on the raspberry pi.

roslocal.sh, rostb3.sh: Scripts to set your ROS IP settings.

CMakeLists.txt: CMake file for the package