Postdoctoral Researcher at the Univeristy of Innsbruck. Robot learning enthusiast

Projects

Ongoing:

Tittle: FLEXible, assistive RObot for customized Production
Participation: 2017 - Today
Role: Investigator
Research: Movement Primitives, Assesement Primitives, Reinforcement Learning
Description: Production of mass customized products is not easy to automate since objects and object positions remain more uncertain compared to mass production scenarios. Uncertainty handling motivates the application of advanced sensor-based control strategies which increases system complexity of robot applications dramatically. A possible solution to this conflict is the concept of task level or skill based programming that will render modern robot systems. Such systems can be applied without safety fence, are easier to program, more applicable and transformable into capable robot assistants. The project will implement a skill based programming framework and will apply it on selected industrial demo scenarios and evaluate research results. The main focus of the project is the application of methods to acquire process information by worker monitoring and thus make the robot assistants self-learning.

Tittle: Robots Understanding Their Actions by Imagining Their Effect
Participation: 2018 - Today
Role: Investigator
Research: Reinforcement Learning of Actions
Description: Imagine seeks to enable robots to understand the structure of their environment and how it is affected by its actions. “Understanding” here means the ability of the robot (a) to determine the applicability of an action along with parameters to achieve the desired effect, and (b) to discern to what extent an action succeeded, and to infer possible causes of failure and generate recovery actions. More information can be found here

Tittle: Sustainable and Reliable Robotics for Part Handling in Manufacturing Automation
Participation: 2013 - 2107
Role: Researcher
Research: Model Learning for Control, Robotic Skills