TypeFly aims to generate robot task plan using large language model (LLM) and our custom programming language MiniSpec. Link to our full Paper and webpage.
Also, check out the demo video here: Demo 1: Find edible or drinkable items, Demo 2: Find a specific chair.
TypeFly works with DJI Tello drone by default. Since Tello drone requires your device to connect to its wifi and TypeFly requires Internet connection, you need to have both wifi adapter and ethernet adapter to run TypeFly.
To support other drones, you need to implement the DroneWrapper interface in controller/abs/drone_wrapper.py.
TypeFly uses YOLOv8 to generate the scene description. We provide the implementation of gRPC YOLO service and a optional http router to serve as a scheduler when working with multiple drones. We recommand using docker to run the YOLO and router. To deploy the YOLO servive with docker, please install the Nvidia Container Toolkit, then run the following command:
make SERVICE=yolo buildOptional: To deploy the router, please run the following command:
make SERVICE=router buildTo play with the TypeFly web UI, please run the following command:
make typeflyThis will start the web UI at http://localhost:50001 with your default camera (please make sure your device has a camera) and a virtual drone wrapper. You should be able to see the image capture window displayed with YOLO detection results. You can test the planning ability of TypeFly by typing in the chat box.
To work with a real drone, please disable the --use_virtual_cam flag in Makefile.
Here we assume your YOLO and router are deployed on the same machine running the TypeFly webui, if not, please define the environment variables VISION_SERVICE_IP, which is the IP address where you deploy your YOLO (or router) service, before running the webui.
Here are some examples of task descriptions, the [Q] prefix indicates TypeFly will output an answer to the question:
Can you find something edible?Can you see a person behind you?[Q] Tell me how many people you can see?