Merge pull request #65 from TangmereCottage/master

Add intro to SLAM/NAV to README and clarify function of the launch command

README.md

@@ -66,6 +66,7 @@ Together, let's push the boundaries of what's possible with the Unitree Go2 and
 
 
 ## System requirements
+
 Tested systems and ROS2 distro
 |systems|ROS2 distro|Build status
 |--|--|--|
@@ -92,30 +93,27 @@ cd ..
 NOTE 1: check for any error messages, and do not disregard them. If `pip install` does not complete cleanly, various features will not work. For example, `open3d` does not yet support `python3.12` and therefore you will need to set up a 3.11 `venv` first etc.
 
 
-Install `rust` language support in your system: [instructions](https://www.rust-lang.org/tools/install) 
-
-After, you need to install 1.79 version of the cargo
-
-```
+Install `rust` language support following these [instructions](https://www.rust-lang.org/tools/install). Then, install version 1.79 of `cargo`, the `rust` package manager.
+```shell
 rustup install 1.79.0
 rustup default 1.79.0
 ```
 
-
-`cargo` should work in terminal 1.79 version
+`cargo` should now be availible in the terminal:
 ```shell
 cargo --version
 ```
 
-Build `go2_ros_sdk`. You need to have `ros2` and `rosdep` installed. If you do not: [instructions](https://docs.ros.org/en/humble/Installation.html). Then:
+Build `go2_ros_sdk`. You need to have `ros2` and `rosdep` installed. If you do not, follow these [instructions](https://docs.ros.org/en/humble/Installation.html). Then:
 ```shell
 source /opt/ros/$ROS_DISTRO/setup.bash
 rosdep install --from-paths src --ignore-src -r -y
 colcon build
 ```
 
 ## Usage
-Don't forget to set up your Go2 robot in Wifi-mode and obtain the IP. You can use the mobile app to get it, go to Device -> Data -> Automatic Machine Inspection and look for STA Network: wlan0.
+
+Don't forget to set up your Go2 robot in Wifi-mode and obtain the IP. You can use the mobile app to get it. Go to Device -> Data -> Automatic Machine Inspection and look for STA Network: wlan0.
 
 ```shell
 source install/setup.bash
@@ -124,17 +122,33 @@ export CONN_TYPE="webrtc"
 ros2 launch go2_robot_sdk robot.launch.py
 ```
 
-## Real time image detection and tracking
+The `robot.launch.py` code starts many services/nodes simultaneously, including 
+
+* robot_state_publisher
+* ros2_go2_video (front color camera)
+* pointcloud_to_laserscan_node
+* go2_robot_sdk/go2_driver_node
+* go2_robot_sdk/lidar_to_pointcloud
+* rviz2
+* `joy` (ROS2 Driver for Generic Joysticks and Game Controllers)
+* `teleop_twist_joy` (facility for tele-operating Twist-based ROS2 robots with a standard joystick. Converts joy messages to velocity commands) 
+* `twist_mux` (twist_multiplexer with source prioritization) 
+* foxglove_launch (launches the foxglove bridge)
+* slam_toolbox/online_async_launch.py
+* av2_bringup/navigation_launch.py
 
+When you run `robot.launch.py`, `rviz` will fire up, lidar data will begin to accumulate, the front color camera data will be displayed too (typically after 4 seconds), and your dog will be waiting for commands from your joystick (e.g. a X-box controller). You can then steer the dog through your house, e.g., and collect lidar mapping data. 
 
-This capability is directly based on [J. Francis's work](https://github.com/jfrancis71/ros2_coco_detector). Once you have launched the sdk, the color image data will be available at `go2_camera/color/image`. In another terminal enter:
+## Real time image detection and tracking
+
+This capability is directly based on [J. Francis's work](https://github.com/jfrancis71/ros2_coco_detector). Launch the `go2_ro2_sdk`. After a few seconds, the color image data will be available at `go2_camera/color/image`. On another terminal enter:
 
 ```bash
 source install/setup.bash
 ros2 run coco_detector coco_detector_node
 ```
 
-There will be a short delay the first time the node is run for PyTorch TorchVision to download the neural network. You should see a downloading progress bar. This network is then cached for subsequent runs.
+There will be a short delay the first time the node is run for PyTorch TorchVision to download the neural network. You should see a download progress bar. TorchVision cached for subsequent runs.
 
 On another terminal, to view the detection messages:
 ```shell
@@ -150,32 +164,33 @@ ros2 run image_tools showimage --ros-args -r /image:=/annotated_image
 ```
 
 Example Use:
-
 ```shell
 ros2 run coco_detector coco_detector_node --ros-args -p publish_annotated_image:=False -p device:=cuda -p detection_threshold:=0.7
 ```
 
 This will run the coco detector without publishing the annotated image (it is True by default) using the default CUDA device (device=cpu by default). It sets the detection_threshold to 0.7 (it is 0.9 by default). The detection_threshold should be between 0.0 and 1.0; the higher this number the more detections will be rejected. If you have too many false detections try increasing this number. Thus only Detection2DArray messages are published on topic /detected_objects.
 
 ## 3D map generation
-To save the map, you need to:
+
+To save the map, `export` the following:
 
 ```shell
 export MAP_SAVE=True
 export MAP_NAME="3d_map"
 ```
 
-Every 10 seconds, the map will be save to root folder of the repo.
+Every 10 seconds, a map will be saved to the root folder of the repo.
 
 ## Multi robot support 
 If you want to connect several robots for collaboration:
 
-```
+```shell
 export ROBOT_IP="robot_ip_1, robot_ip_2, robot_ip_N"
 ```
 
 ## Switching between webrtc connection (Wi-Fi) to CycloneDDS (Ethernet)
-```
+
+```shell
 export CONN_TYPE="webrtc"
 ```
 or