This repository contains the code for a perception stack designed and developed for a human tracking robot. The perception stack utilizes deep learning-based systems for person detection and re-identification.
The following dependencies are required to run the code:
- PyTorch
- OpenCV
- NumPy
Create a virtual environment in the root directory:
pip install virtualenv
virtualenv <env name>
To activate the environment:
source <env name>/bin/activate
Clone the repository:
git clone https://github.com/Ashwij3/Human_following_robot.git
To install the dependencies, run the following command:
pip install -r requirements.txt
To use the perception stack, run the following command:
Copy code
python3 scripts/main.py
The perception stack utilizes the following algorithms:
- YOLOv7 for human detection and instance segmentation
- SuperPoint for feature extraction and matching
The implemented perception stack achieves accurate identification of the target individual, allowing for effective human tracking by the robot.
Human_following_demo.mp4
The code in this repository is based on the following research papers: