Topic: ‘Interactive Robot Learning’, see job description below

Location: TU Delft, The Netherlands

Duration: 24 months

Application deadline: March 15th 2021

Starting date: at the latest September 2021

Salary: EUR 3.491 – EUR 4.402

For more details see https://www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details?jobId=1965

Applications need to be submitted via the website above. For more information about this vacancy, please contact Jens Kober, Associate Professor, email: mailto:J.Kober@tudelft.nl

*Job description*

Programming and re-programming robots is extremely time-consuming and expensive, which presents a major bottleneck for new industrial, agricultural, care, and household robot applications. The goal of this project is to enable robots to learn how to perform manipulation tasks from few human demonstrations, based on novel interactive machine learning techniques. Robot learning will no longer rely on initial demonstrations only, but it will effectively use additional user feedback to continuously optimize the task performance. It will enable the user to directly perceive and correct undesirable behavior and to quickly guide the robot toward the target behavior. You will explore one or several aspects of interactive robot learning: learning force-interaction skills with user inputs, requesting additional advice, interactive imitation and reinforcement learning for sequences, interactive inverse reinforcement learning, and evaluating how humans prefer to teach robots. You will evaluate the developed approaches with generic real-world robotic force-interaction tasks related to handling and (dis)assembly. You will demonstrate the potential of the newly developed teaching framework with challenging bi-manual tasks and a final user study evaluating how well novice human operators can teach novel tasks to a robot.

The Postdoc positions are in the context of the project "Teaching Robots Interactively" (TERI), funded by the European Research Council as ERC Starting Grant.

*Requirements*

You have a PhD degree in systems and control, robotics, applied mathematics, artificial intelligence, machine learning, or a related subject. You must have strong analytical skills and must be able to work at the intersection of several research domains. Experience with real robot applications, bi-manual robots, interactive learning, and/or user studies is a plus.

You must have demonstrated ability to conduct high-quality research according to international standards, as demonstrated by publications in international, high-quality journals. A very good command of the English language is required, as well as excellent communication skills.