Computer Vision resources and packages for the Robocup@Home Competition.
To launch vision nodes, it is recommended to use the dockerfiles according to the computer's resources (CUDA):
Without cuda:
make vision.build
make vision.create
make vision.shell
With cuda:
make vision.build.cuda
make vision.create.cuda
make vision.shell
For the receptionist task, it was required to recognize people, identify empty seats from either chairs or couches and detect if a person is standing in front of a robot. Hence, two nodes where developed. One to perform person or object detection procedures and one for the face-recognition analysis. These functionalities where accessed through three services:
Person Detection
Service topic: /vision/check_person
Face Recognition
Service topic: /vision/new_name
Seat Finding
Service topic: /vision/find_seat
Launch File
roslaunch vision receptionist.launch
For several tasks, it is necessary to identify a person and track their position. Hence a node was developed using YOLO and a REID model.
Service topic: /vision/change_person_tracker_state
Launch File
roslaunch vision tracking.launch FLIP_IMAGE:=false
For the GPSR task, there are several commands that require computer vision algorithms. Some involve identifying a person who meets a specific pose or shirt color, and some involving counting people who meet this criteria. Therefore, the person command node has several services for this commands. It uses YOLOv8 for person detection, Mediapipe for pose detection and a custom model for shirt color detection.
Person counting
Service topic (bool): /vision/start_counting
Service topic (string): /vision/end_counting
Person finding
Service topic (string): /vision/find_pose
Shelf detection