Add README.md

CMakeLists.txt

@@ -11,7 +11,6 @@ find_package(ament_cmake REQUIRED)
 find_package(rclcpp REQUIRED)
 find_package(geometry_msgs REQUIRED)
 find_package(nav_msgs REQUIRED)
-find_package(phnx_msgs REQUIRED)
 find_package(OpenCV 4.2.0 REQUIRED)
 find_package(visualization_msgs REQUIRED)
 
@@ -27,7 +26,6 @@ set(dependencies
         rclcpp
         geometry_msgs
         nav_msgs
-        phnx_msgs
         OpenCV
         visualization_msgs
 )

README.md

@@ -1,47 +1,38 @@
-An opinionated ROS2 C++ node template, optimised for ISC.
-
-# Instructions
-
-1. Clone repo inside your workspaces src directory (Ex. phnx_ws/src)
-2. `rosdep install --from-paths . --ignore-src -r -y` to install deps
-3. `colcon build` to make sure the repo builds before you mess with it
-4. Replace the following in both file names and code exactly and consistently. 
-   1. obj_tracker: Replace with the package name. Use snake case. Ex. `data_logger`
-   2. ObjTrackerNode: Replace with the node name. Use Pascal case. Ex. `DataLogger`
-5. `colcon build` again. If it builds, you are done
-6. Rename outer folder
-7. Review the optional dependencies, and remove what you do not need
-
-# Dependencies
-Some common extra dependencies are included. Review them and remove what you don't need.
-These are marked with TODO_EXTRA.
-
-# Features
-
-- Unit tests
-- ROS-Industrial github CI (will test units and lints)
-- C++ formatting via clangformat
-- A selection of sane lints
-- A single node setup in a multithreaded executor
-
-# File structure
-
-```
-.
-├── include
-│   └── obj_tracker
-│       └── ObjTrackerNode_node.hpp
-├── package.xml
-├── README.md
-├── src
-│   ├── ObjTrackerNode.cpp
-│   └── ObjTrackerNode_node.cpp
-└── tests
-    └── unit.cpp
-```
-
-ObjTrackerNode_node: Source files for the ROS2 node object itself, and only itself
-
-ObjTrackerNode.cpp: Source for the main function of the node, and only the main function
-
-tests/unit.cpp: Example file for unit tests. This is linked to the node and ros, so both can be used
+# obj_tracker
+From package '[obj_tracker](https://github.com/ISC-Project-Phoenix/obj_tracker)'
+# File
+`./src/ObjTrackerNode.cpp`
+
+## Summary 
+ Generic Multiple Object Tracker (MOT) node for ROS2. Obj_tracker tracks PoseArrays over time, both smoothing the pose
+and maintaining indentity. It does this by predicting with Kalman filters, then associating tracks with detections
+by solving the resulting assignment problem.
+
+## Topics
+
+### Publishes
+- `/tracks`: Array of Filtered poses
+
+### Subscribes
+- `/object_poses`: Array of Poses to filter
+
+## Params
+- `max_frames_missed`: Number of updates a tracker is allowed to predict without being matched to a detection.
+Smaller numbers will be vulerable to flaky detections, larger values can stick around too long after detection leaves.
+- `max_dist`: Max distince in meters allowed between a track and detection before they are considered to not be associated.
+This will need to be larger for data with high amplitude in its noise, but that risks swapping tracks between detections.
+
+- `prediction_cov`: Scalar used for the diagonal of the prediction covarience matrix of the kalman filters. Lower values weight the filter
+more towards predictions.
+
+- `measure_cov`: Scalar used for the diagonal of the measurement covarience matrix of the kalman filters. Lower values weight the filter
+more towards measurements.
+
+- `inital_vx`: Scalar used for the inital x velocity state in the kalman filters. Use this to bias the filters inital predictions to
+follow object motion if you are moving forward or backwards.
+
+- `test_latency`: Outputs the latency of the node as logs if true.
+
+- `visualize_ids`: Publishes id markers in rviz if true.
+
+

obj_tracker.doctor.toml

@@ -0,0 +1,70 @@
+#ROS package you are documenting
+package_name = "obj_tracker"
+repo = "https://github.com/ISC-Project-Phoenix/obj_tracker"
+
+#You can have multiple nodes in one package
+[[nodes]]
+node_name = 'obj_tracker'
+#Relitive to this file
+source_file = ['./src/ObjTrackerNode.cpp']
+summary = '''
+Generic Multiple Object Tracker (MOT) node for ROS2. Obj_tracker tracks PoseArrays over time, both smoothing the pose
+and maintaining indentity. It does this by predicting with Kalman filters, then associating tracks with detections
+by solving the resulting assignment problem.
+'''
+
+#Your published topics (optional)
+[[nodes.publishes]]
+name = '/tracks'
+description = 'Array of Filtered poses'
+
+#Your subscribed topics (optional)
+[[nodes.subscribes]]
+name = '/object_poses'
+description = 'Array of Poses to filter'
+
+#Your node parameters (optional)
+[[nodes.params]]
+name = 'max_frames_missed'
+description = '''Number of updates a tracker is allowed to predict without being matched to a detection.
+Smaller numbers will be vulerable to flaky detections, larger values can stick around too long after detection leaves.'''
+
+[[nodes.params]]
+name = 'max_dist'
+description = '''
+Max distince in meters allowed between a track and detection before they are considered to not be associated.
+This will need to be larger for data with high amplitude in its noise, but that risks swapping tracks between detections.
+'''
+
+[[nodes.params]]
+name = 'prediction_cov'
+description = '''
+Scalar used for the diagonal of the prediction covarience matrix of the kalman filters. Lower values weight the filter
+more towards predictions.
+'''
+
+[[nodes.params]]
+name = 'measure_cov'
+description = '''
+Scalar used for the diagonal of the measurement covarience matrix of the kalman filters. Lower values weight the filter
+more towards measurements.
+'''
+
+[[nodes.params]]
+name = 'inital_vx'
+description = '''
+Scalar used for the inital x velocity state in the kalman filters. Use this to bias the filters inital predictions to
+follow object motion if you are moving forward or backwards.
+'''
+
+[[nodes.params]]
+name = 'test_latency'
+description = '''
+Outputs the latency of the node as logs if true.
+'''
+
+[[nodes.params]]
+name = 'visualize_ids'
+description = '''
+Publishes id markers in rviz if true.
+'''