This is the project-based learning lab, you must finish all the lab exercises and make a final project meet with criteria to complete the lab.
As you know, our lab focus on research topic is Autonomous robot and SLAM. Here some types of equipment will help you to finish this lab project.
- Industrial robotics arm UR10e (Link tutorial: https://tribien.gitbook.io/ur-robot-tutorial/)
- Camera: Intel realsense D435 (https://www.intelrealsense.com/depth-camera-d435/, https://intelrealsense.github.io/librealsense/python_docs/_generated/pyrealsense2.html)
To prepare the Lab SSA2022 in Python environment, follow the steps below:
- Download PyCharm integrated development environment or Anaconda package and environment manager.
- Download Python 3.7 or later
- Download get-pip.py and run the following commands in PyCharm terminal:
- python get-pip.py Pip tool to install Pip Python package
- pip install pyrealsense2 Intel RealSense cross-platform open-source API
- pip install numpy Fundamental package for scientific computing
- pip install matplotlib 2D plotting library producing publication quality figures
- pip install opencv-python OpenCV packages for Python
- pip install tensorflow Tensorflow packages for Machine learning lab
some of these packages are not directly used here, but maybe useful in other examples
- Lab 1: Hand-on Robotics hardware (10%)
- Lab 2: Machine Learning in Image Processing (10%)
- Lab 3. Meta Heuristic Algorithms (10%)
- Clear and focused purpose (10%)
- Data collection and processing methods (10%)
- Integrated machine learning algorithm (10%)
- Integrated smart algorithms (10%)
- Project demonstrates significant creativity (20%)
- Demonstration on real-hardware (10%)