Koc, O.; Maeda, G.; Peters, J. (2018). “Online optimal trajectory generation for robot table tennis”. Robotics and Autonomous Systems (RAS). … More
Category: Video
Human-robot joint skill learning
One of the most successful recipes in robot learning is to initialize the robot with a *good policy* via imitation … More
Presenting at the Conference on Robot Learning (CoRL) 2017
November 2017. I am presenting our most recent work at the 1st Annual Conference on Robot Learning (CoRL 2017). The paper can … More
Active Incremental Learning of Robot Movement Primitives (PMLR/CoRL 2017)
Robots that can be programmed by non-technical users must be capable of learning new tasks incrementally, via demonstrations. This poses the … More
Ergonomics in robot trajectory generation (IROS 2017)
In collaboration with the Flowers Group in Inria, we addressed the problem of how to generate robot motions that are … More
Optimizing the Mapping from Human Observations to Robot Kinematics (IEEE RA-L 2016)
Imitation learning is useful to endow robots with skills that are difficult, if not impossible, to program by hand. … More
Phase Estimation of Human Movements for Responsive Human-Robot Collaboration (ISRR 2015)
While probabilistic models are useful to classify and infer trajectories, a common problem is that their construction usually requires the … More
Interaction ProMPs (IJRR 2017, AURO 2016, HUMANOIDS 2014)
Interaction Probabilistic Movement Primitive (Interaction ProMP) is a probabilistic framework based on Movement Primitives that allows for both human action … More
