NB: This is an advertisement for a master thesis hosted at the CREATE Lab (academic thesis project), and will be collaborating with Embodied AI towards future industrial applications

Learning based controllers (specifically those based on imitation learning) present a promising direction towards autonomous applications in real world situations. Despite these advances, robots struggle on a number of fronts: long horizon tasks, recovery, large task adaptations, etc. 

For practical deployment, an intermediate step is considered human-supervised semi-autonomy, where a robot is able to execute small segments of autonomous tasks, which are coordinated by a human. In this project, you will explore how to blend cutting edge learning algorithms with teleoperation. 

Directions of the project (not all are part of the scope of the project, but depending on the progress, this can be varied): 

1. Explore state of the art learning based algorithm on real robots

2. Implement and experiment on different transition methods between autonomous and teleoperated motion.

Useful skills / prior experience to have:

• Working with real robots (prototyped and purchased)

• Implementation of learning based controllers

• Software and embedded hardware interfacing