Marco Ewerton

Quick Info

Research Interests

Artificial Intelligence, Machine Learning, Robotics, Imitation Learning, Human-Robot Interaction, Motor Skill Learning

More Information

Curriculum Vitae Publications Google Citations

Contact Information

Mail. Marco Ewerton
TU Darmstadt, FG IAS,
Hochschulstr. 10, 64289 Darmstadt
Office. Room E226, Building S2|02
work+49-6151-16-20073

Marco Ewerton is a Ph.D. student at the IAS under the supervision of Guilherme Maeda and Jan Peters since January 2015. He works on the BIMROB project, which investigates how humans and robots can improve their movements by interacting with each other.

He obtained his master's degree in Electrical and Information Engineering from the TU Darmstadt in 2014. His master's thesis work focused on modeling human-robot interaction with probabilistic movement representations (video here).

From April 2012 to December 2013, he was a research assistant at the IAS under the supervision of Heni Ben Amor. During that time, the main topics of Marco's work were "3D reconstruction from multiple Kinect cameras" and "Human-Robot Interaction".

Research Interests

Artificial Intelligence, Machine Learning, Robotics, Imitation Learning, Human-Robot Interaction, Motor Skill Learning

Key References

  1. Ewerton, M.; Neumann, G.; Lioutikov, R.; Ben Amor, H.; Peters, J.; Maeda, G. (2015). Learning Multiple Collaborative Tasks with a Mixture of Interaction Primitives, Proceedings of the International Conference on Robotics and Automation (ICRA), pp.1535--1542.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex] . Best Paper Award Finalist, Best Student Paper Award Finalist and Best Service Robotics Paper Award Finalist
  2. Ewerton, M.; Maeda, G.J.; Peters, J.; Neumann, G. (2015). Learning Motor Skills from Partially Observed Movements Executed at Different Speeds, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), pp.456--463.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]
  3. Ewerton, M.; Maeda, G.; Neumann, G.; Kisner, V.; Kollegger, G.; Wiemeyer, J.; Peters, J. (2016). Movement Primitives with Multiple Phase Parameters, Proceedings of the International Conference on Robotics and Automation (ICRA), pp.201--206.   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]
  4. Ewerton, M.; Maeda, G.J.; Kollegger, G.; Wiemeyer, J.; Peters, J. (2016). Incremental Imitation Learning of Context-Dependent Motor Skills, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).   See Details [Details]   Download Article [PDF]   BibTeX Reference [BibTex]

Code

Matlab code on Learning Motor Skills from Partially Observed Movements Executed at Different Speeds: code related to the work presented at IROS 2015

Videos

Estimating the phase of the execution of the human movement for human-robot interaction (IROS 2015)

Semi-Autonomous Robots at TU Darmstadt: Learning Multiple Collaborative Tasks (ICRA 2015)

Quick explanation of "Mixture of Interaction Primitives" recorded by Robohub at ICRA 2015

  

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