To train a robot foundation model, we need diverse data. This project aims to utilize simulation to collect that data. The task is to create simulation environments, a data collection method, and a postprocessing pipeline to support the training of foundation models.
- Strong programming
- Strong communication, collaboration, organization, and planning
- Proactive and fast self-learner
- Familiarity with simulation tools (AsaacSim, Unreal Engine, Gazebo)
- Familiarity with machine learning: PyTorch
- Familiarity with software: ROS2, Python, C++, Linux, Bash, Git
- Learn and strengthen the skills above
- Understand the full pipeline required to develop an intelligent robot from start to finish
- Working with senior students and faculty advisors
Not a hard limit. We care more about talent and potential.