This project involves capturing and processing human upper body pose information using the Mediapipe library and transmitting the relevant joint angles to a humanoid robot (NAO) using the NAOqi framework. The goal is to enable the robot to mimic the detected upper body pose of a human.
-
Human Pose Detection:(py3)
- Uses the Mediapipe library to detect and extract key landmarks of the upper body from an input image.
- Landmark coordinates are stored in a text file for further use.
-
Robot Motion Control(py2.7):
- Uses the NAOqi framework to control the motion of a humanoid robot based on the extracted pose information.
- Joint angles are read from the text file and interpolated to mimic the detected upper body pose.
- OpenCV
- Mediapipe
- NAOqi (Python SDK for controlling NAO humanoid robots)
- Ensure all required libraries are installed (
cv2,mediapipe, andnaoqi). - Update all paths
- Run the pose detection component to capture and store upper body pose information, make to sure to use pyhton 3.
- Run the robot motion control component to make the humanoid robot mimic the detected upper body pose, make sure to use python 2.7.
For detailed documentation, including the Denavit-Hartenberg (DH) model of the NAO robot, please refer to ahmedemadtawfik@gmail.com
- Adjust file paths and IP addresses in the code according to your setup.
- Fine-tune time durations in the robot motion code for smoother movements.
- You can make the pose detection capture the landmarks from a video or even LiveFeed