Process robotics data with HPCC Systems

This project was completed during the 2020 HPCC Systems Intern Program by Jack Fields, American Heritage School of Boca/Delray, USA.

Find out about the HPCC Systems Summer Internship Program.

Resources Available to Learn More about this completed project:

Project Description

Process Robotics data with HPCC Systems Platform. Previous intern project by American Heritage High School (AH) student Aramis developed ROS package to collect data from various sensors and spray to HPCC Systems Thor. Aramis also created some ECL code to graph some data with HPCC Systems libraries. In this project we try to go to a further step to process some data. One of the possible area is images collected from the Robotics developed by AH recently. The project will try to train a model with HPCC Systems Machine Learning (ML) General Neural Network (GNN) which support TensorFlow and apply it new data.

If you are interested in this project, please contact the mentors using the details below.

Completion of this project involves:

Producing design documentation
Develop GNN ECL code to train a model
Checked in code
Documentation

Data processing with HPCC Systems involves:

Learning HPCC Systems architecture
Learning ECL
Learning HPCC Systems ML GNN
HPCC Systems GNN (TensorFlow)
- Docker Image
- VirtualBox
- Hyper-V (VHD)
- AWS AMI

Processing image data with HPCC Systems GNN involves:

Collecting images
Pre-processing the images. For example should we need down size the image?
Spraying the image data to thor
Use GNN to train the model. There are lots of works needed here. Mainly find suitable hyper-parameters
Saving the model
Using the model for the new image data.

By the mid term review we would expect you to have:

Sprayed image data to Thor
Written initial ECL code
Trained a model with HPCC Systems GNN with some initial result

Mentor	David De Hilster Contact Details Backup Mentor: Xiaoming Wang Contact Details
Skills needed	Git, CMake Build ROS package HPCC Systems Platform and ECL Python, Unix Bash, Machine Learning, Neural Networks, particularly Convolution Neural Networks (CNN) Kera, TensorFlow Ability to build and test the HPCC system (guidance will be provided). Ability to write test code. Knowledge of ECL is not a requirement since it should be possible to re-use existing code with minimal changes for this purpose. Links are provided below to our ECL training documentation and online courses should you wish to become familiar with the ECL language.
Deliverables	Midterm Sprayed image data to Thor Written initial ECL code Trained a model with HPCC Systems GNN with some initial result End of project Tuning hyperparameters to improve model training. Documentation
Other resources	HPCC Systems website https://hpccros.wordpress.com/ https://github.com/hpcc-systems/GNN https://github.com/hpcc-systems/GPU-Deep-Learning Github repo: https://github.com/Aramist/hpcc-robotics Hands-on Machine Learning with Scikit-Learn Kera & TensorFlow Learning ECL documentation and on-line training courses.

Resources Available to Learn More about this completed project:

Mentor

Skills needed

Deliverables

Other resources