Follow a Track
Before diving into this code, here's a quick heads-up on what you'll need to be familiar with:
- Python Programming: It's important to have a good grasp of Python, especially with concepts
like
functions,loops, andclasses, since the example utilizes these fundamentals. - Asynchronous Programming with asyncio: Familiarity with Python's asyncio for writing concurrent
code using the
async/awaitsyntax. - farm-ng Track Follower Service Overview: This overview provides a base understanding of the gRPC service the client you create will connect to.
- farm-ng Transforms & Poses Overview: This overview provides insight into coordinate frames, transforms, and poses as they pertain to autonomous systems and autonomous navigation.
- farm-ng Tracks & Waypoints Overview: This overview provides insight into compiling poses as waypoints into a Track that can be followed by the Amiga.
The track follower examples will cause the Amiga to drive when the dashboard is in auto mode. Make sure the area is clear before running examples.
You can also run the examples when the Amiga dashboard is not in AUTO READY or AUTO ACTIVE
and see the commands being sent with the red needle on the auto page without the Amiga actually moving.
The Track Follower Example
operates as a standalone Python script,
in which an EventClient to the farm-ng Track Follower service running on an Amiga brain is created.
This script takes in a pre-recorded track and commands the Amiga to follow it.
You can either run this example directly on a brain by ssh'ing in, or use your local PC.
If using your local PC, it should be either connected to the same local network as the brain
or linked to it through tailscale.
Ensure that a farm-ng brain, with a GPS receiver and Oak cameras, is actively running the track follower service.
It is highly recommended to read through the Track Follower Service Overview before running this example.
This will provide insight into the requirements and API for using the track follower service to follow a path.
1. Install the farm-ng Brain ADK package​
2. Install the example's dependencies​
It is recommended to also install these dependencies and run the example in the brain ADK virtual environment.
Setup​
Create a virtual environment
python3 -m venv venv
source venv/bin/activate
Install​
cd py/examples/track_follower
pip install -r requirements.txt
3. Execute the Python script​
To run this script from your PC, you need to update the service_config.json
by modifying the host field with your Amiga brain name.
Please check out Amiga Development 101 for more details.
python main.py --service-config service_config.json --track <path-to-your-track>
# Replace <path-to-your-track> to the actual file path to your track
There's an example to teach you how to record your own track here.
If everything worked correctly you should now see a large stream of text come up in your terminal!
4. Code Overview​
In this example we use the EventClient with the request_reply method to set a track
(/set_track) to be followed.
We then command the track follower to follow the set track (/start).
async def set_track(service_config: EventServiceConfig, track: Track) -> None:
"""Set the track of the track_follower.
Args:
service_config (EventServiceConfig): The track_follower service config.
track (Track): The track for the track_follower to follow.
"""
print(f"Setting track:\n{track}")
await EventClient(service_config).request_reply("/set_track", TrackFollowRequest(track=track))
async def start(service_config: EventServiceConfig) -> None:
"""Follow the track.
Args:
service_config (EventServiceConfig): The track_follower service config.
"""
print("Sending request to start following the track...")
await EventClient(service_config).request_reply("/start", Empty())
async def main(service_config_path: Path, track_path: Path) -> None:
"""Run the track_follower track example. The robot will drive the pre-recorded track.
Args:
service_config_path (Path): The path to the track_follower service config.
"""
# Extract the track_follower service config from the JSON file
service_config: EventServiceConfig = proto_from_json_file(service_config_path, EventServiceConfig())
# Read the track and package in a Track proto message
track: Track = proto_from_json_file(track_path, Track())
# Send the track to the track_follower
await set_track(service_config, track)
# Follow the track
await start(service_config)
We also use the subscribe method to receive and stream the track follower state.
async def stream_track_state(service_config_path: Path) -> None:
"""Stream the track_follower state.
Args:
service_config_path (Path): The path to the track_follower service config.
"""
# Brief wait to allow the track_follower to start (not necessary in practice)
await asyncio.sleep(1)
print("Streaming track_follower state...")
# create a client to the camera service
config: EventServiceConfig = proto_from_json_file(service_config_path, EventServiceConfig())
message: TrackFollowerState
async for event, message in EventClient(config).subscribe(config.subscriptions[0], decode=True):
print("###################")
print(message)
We use the asyncio.gather method to allow running the two tasks,
(1) setting the track follower to follow the track and (2) streaming the track follower state,
simultaneously and asynchronously.
async def run(args) -> None:
tasks: list[asyncio.Task] = [
asyncio.create_task(main(args.service_config, args.track)),
asyncio.create_task(stream_track_state(args.service_config)),
]
await asyncio.gather(*tasks)
if __name__ == "__main__":
parser = argparse.ArgumentParser(prog="amiga-track-follower")
parser.add_argument("--service-config", type=Path, required=True,
help="The track_follower service config.")
parser.add_argument("--track", type=Path, required=True,
help="The filepath of the track to follow.")
args = parser.parse_args()
loop = asyncio.get_event_loop()
loop.run_until_complete(run(args))
Congrats you are done!
To run this example, you must activate the auto control mode on your Amiga via the dashboard.
We highly recommend to have some basic knowledge about
asyncio.