Publications

Journal Articles

  1. Celemin, C.; Maeda, G.; Ruiz-del-Solar, J.; Peters, J.; Kober, J. (Conditionally accepted). “Reinforcement Learning of Motor Skills using Policy Search and Human Corrective Advice”. The International Journal of Robotics Research (IJRR).
  2. Koc, O.; Maeda, G.; Peters, J. (2018). “Online optimal trajectory generation for robot table tennis”. Robotics and Autonomous Systems (RAS). vol. 105, pp. 121–137. [pdf][BibTeX]
  3. Ewerton, M.; Rother, D; Weimar, J.; Kollegger, G.; Wiemeyer, J.; Peters, J.; Maeda, G. (2018). “Assisting Movement Training and Execution with Visual and Haptic Feedback”, Frontiers in Neurorobotics.[article][BibTeX]
  4. Lioutikov, R.; Neumann, G.; Maeda, G.; Peters, J. (2017). “Learning Movement Primitive Libraries through Probabilistic Segmentation”, International Journal of Robotics Research (IJRR). vol. 36. no 8, pp. 879-894. [pdf][BibTeX]
  5. Maeda, G.; Ewerton, M; Neumann, G.; Lioutikov, R.; Peters, J. (2017). “Phase Estimation for Fast Action Recognition and Trajectory Generation in Human-Robot Collaboration”, International Journal of Robotics Research (IJRR). vol. 36, no 13-14, pp. 1579–1594. [pdf][BibTeX]
  6. Maeda, G.; Ewerton, M; Koert, D.; Peters, J. (2016). “Acquiring and Generalizing the Embodiment Mapping from Human Observations to Robot Skills”, IEEE Robotics and Automation Letters (RA-L), vol. 1, no 2, pp. 784–791. [pdf][BibTeX]
  7. Maeda, G.; Neumann, G.; Ewerton, M; Lioutikov, R.; Kroemer, O.; Peters, J. (2017). “Probabilistic Movement Primitives for Coordination of Multiple Human-Robot Collaborative Tasks”, Autonomous Robots (AURO), vol. 41, no. 3, pp. 593–612. [pdf][BibTeX]
  8. Maeda, G.; Manchester, I.; Rye, D. (2015). “Combined ILC and disturbance observer for the rejection of near-repetitive disturbances, with application to excavation”, IEEE Transactions on Control Systems Technology, vol. 23, no. 5, pp. 1754–1769. [pdf][BibTeX]
  9. Sato, K.; Maeda, G. (2009). “A practical control method for precision motion. Improvement of NCTF control method for continuous motion control”, Precision Engineering, vol. 33, no. 2, pp. 175–186. [pdf][BibTeX]
  10. Maeda, G.; Sato, K. (2008). “Practical control method for ultra-precision positioning using a ballscrew mechanism”, Precision Engineering, vol. 32, no. 4, pp. 309–318. [pdf][BibTeX]
  11. Sato, K.; Maeda, G. (2008). “Practical ultraprecision positioning of a ball screw mechanism”, International Journal of Precision Engineering and Manufacturing, vol. 9, no. 2, pp. 44–49.[BibTeX]
  12. Maeda, G.; Sato, K.; Hashizume, H.; Shinshi, T. (2006). “Control of an XY nano–positioning table for a compact nano-machine tool”, JSME International Journal Series C, vol. 49, no. 1, pp. 21–27. [pdf][BibTeX]. Winner of the Outstanding Young Researcher Award.

Book Chapter

  1. Lioutikov, R.; Kroemer, O.; Peters, J.; Maeda, G. (2016). “Learning Manipulation by Sequencing Motor Primitives with a Two-Armed Robot”, Advances in Intelligent Systems and Computing. Proceedings of the 13th International Conference on Intelligent Autonomous Systems (IAS), pp. 1601–1611. [pdf][BibTeX].
  2. Maeda, G.; Rye, D.; Singh, S. (2014). “Iterative autonomous excavation”, In Field and Service Robotics, Series: Springer Tracts in Advanced Robotics, pp. 369–382. [pdf][BibTeX]

Peer-Reviewed Conference Papers

  1. Maeda, G.; Koc, O.; Morimoto, J. (2018). “Reinforcement Learning of Phase Oscillators for Fast Adaptation to Moving  Targets”, Proceedings of Machine Learning Research (PMLR). Conference on Robot Learning (CoRL) [BibTeX]
  2. Lioutikov, R; Maeda, G.; Veiga, F.; Kersting, K.; Peters. J.  (2018). “Inducing Probabilistic Context-Free Grammars for the Sequencing of Robot Movement Primitives”, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). [pdf][BibTeX]
  3. Koert, D; Maeda, G.; Neumann, G.; Peters. J. (2018). “Learning Coupled Forward-Inverse Models with Combined Prediction Errors”, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). [BibTeX]
  4. Maeda, G.; Ewerton, M.; Osa, T; Busch, B.; Peters, J. (2017). “Active Incremental Learning of Robot Movement Primitives”, Proceedings of Machine Learning Research (PMLR), 78: Conference on Robot Learning (CoRL), pp. 37–46. [pdf][BibTeX]
  5. Busch, B.; Maeda, G.; Mollard, Y.; Demangeat, M.; Lopes, M. (2017). “Postural Optimization for an Ergonomic Human-Robot Interaction”, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
  6. Maeda, G.; Maloo, A.; Ewerton, M; Lioutikov, R; Peters, J. (2016). “Anticipative Interaction Primitives for Human-Robot Collaboration”, AAAI Fall Symposium Series. Shared Autonomy in Research and Practice, Arlington, VA, USA. [pdf][BibTeX]
  7. Koc, O.; Maeda, G.; Peters, J. (2016). “A New Trajectory Generation Framework in Robotic Table Tennis”, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), pp. 3750–3756. [pdf][BibTeX]
  8. Koert, D.; Maeda, G.; Lioutikov, R.; Neumann, G. & Peters, J. (2016). “Demonstration Based Trajectory Optimization for Generalizable Robot Motions”, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2016, 515-522. [pdf][BibTeX]
  9. Ewerton, M; Maeda, G.; Neumann, G.; Kisner, V.; Kollegger, G.; Wiemeyer, J.; Peters. J. (2016). “Movement Primitives with Multiple Phase Parameters”, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pp. 201–206. [pdf][BibTeX]
  10. Koc, O.; Maeda, G.; Neumann, G.; Peters, J. (2015). “Optimizing Robot Striking Movement Primitives with Iterative Learning Control”, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), pp. 80–87. [pdf][BibTeX]
  11. Lioutikov, R.; Neumann, G.; Maeda, G.; Peters, J. (2015). “Probabilistic Segmentation Applied to an Assembly Task”, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), pp. 533–540. [pdf][BibTeX]
  12. Maeda, G.; Neumann, G.; Ewerton, M.; Lioutikov, R.; Peters, J. (2015). “A Probabilistic Framework for Semi-Autonomous Robots Based on Interaction Primitives with Phase Estimation”, International Symposium of Robotics Research (ISRR). [pdf][BiBTeX]
  13. Ewerton, M.; Maeda, G.; Peters, J.; Neumann, G. (2015). “Learning Motor Skills from Partially Observed Movements Executed at Different Speeds”, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 456–463. [pdf][BibTeX]
  14. 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 IEEE International Conference on Robotics and Automation (ICRA), pp. 1535–1542. Best Paper Award Finalist, Best Student Paper Award Finalist and Best Service Robotics Paper Award Finalist.  [pdf][BibTeX]
  15. Maeda, G.; Ewerton, M.; Lioutikov, R.; Ben Amor, H.; Peters, J.; Neumann, G. (2014). “Learning Interaction for Collaborative Tasks with Probabilistic Movement Primitives”, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), pp. 527–534. [pdf][BibTeX]
  16. Maeda, G.; Rye, D. (2012). “Learning disturbances in autonomous excavation”, in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 2599–2605. [pdf][BibTeX]
  17. Maeda, G.; Rye, D.; Singh, S. (2012). “Iterative autonomous excavation”, in The 8th International Conference on Field and Service Robotics (FSR). [pdf][BibTeX]
  18. Maeda, G.; Singh, S.; Rye, D. (2011). “Improving operational space control of heavy manipulators via open-loop compensation”, in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 725–731.
  19. Maeda, G.; Singh, S.; Durrant-Whyte, H. (2011). “A tuned approach to feedback motion planning with RRT’s under model uncertainty”, in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pp. 2288–2294.
  20. Maeda, G.; Singh, S.; Durrant-Whyte, H. (2010). “Feedback motion planning approach for nonlinear control using gain scheduled RRT’s”, in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 119–126.
  21. Sato, K.; Maeda, G. (2007). “Simple and practical control method for ultra-precision positioning: Application to a ballscrew mechanism”, in Proc. of ASPE Annual Meeting, pp. 179–182.

Workshop Submissions

  1. Celemin, C.; Maeda, G.; Kober, J.; Ruiz-del-Solar, J. (2017). “Human Corrective Advice in the Policy Search Loop”, Workshop: Human-in-the-loop robotic manipulation: on the influence of the human role (IROS).
  2. Ewerton, M.; Maeda, G.; Rother, D.; Weimar, J.; Lotter, L.; Kollegger, G.; Wiemeyer, J.; Peters, J. (2017). “Assisting the practice of motor skills by humans with a probability distribution over trajectories”, Workshop: Human-in-the-loop robotic manipulation: on the influence of the human role (IROS).
  3. Ewerton, M.; Kollegger, G.; Maeda, G.; Wiemeyer, J.; Peters, J. (2017). “Iterative Feedback basierte Korrekturstrategien”, Workshop: beim Bewegungslernen von Mensch-Roboter-Dyaden, DVS Sportmotorik 2017.
  4. Maeda, G.; Maloo, A.; Ewerton, M.; Lioutikov, R.; Peters, J. (2016). “Proactive Human-Robot Collaboration with Interaction Primitives”, International Workshop on Human-Friendly Robotics (HFR), Genoa, Italy.

Supervised and Co-supervised Theses

  1. Koc, O. (2018). “Optimal Trajectory Generation and Learning Control for Robot Table Tennis”, PhD Thesis, TU Darmstadt. Main supervisor: Peters, J.; co-supervisor: Maeda, G.
  2. Lioutikov, R. (2018), “Parsing Motion and Composing Behavior for Semi-Autonomous Manipulation”, Ph.D. thesis, TU Darmstadt. Main supervisor: Peters, J.; co-supervisor: Maeda, G.
  3. Lolkes, C. (2017). “Incremental Imitation Learning with Estimation of Uncertainty”, Bachelor Thesis, TU Darmstadt.
  4. Koert, D. (2016). “Combining Human Demonstrations and Motion Planning for Movement Primitive Optimization”, Master Thesis, TU Darmstadt.
  5. Alte, D. (2016). “Control of a robotic arm using a low-cost BCI”, Bachelor Thesis, TU Darmstadt.
  6. Koert, D. (2015). “Inverse Kinematics for Optimal Human-Robot Collaboration”, Honors Thesis, TU Darmstadt.
  7. Ewerton, M. (2014). “Modeling Human-Robot Interaction with Probabilistic Movement Representations”, Master Thesis, TU Darmstadt.

Patents

  1. Suzuki, S.; Maeda, G. “Offset printing method and apparatus” 2012, US Patent 13/265,653.
  2. Suzuki, S.; Maeda, G. “Inking method and apparatus thereof” 2011, US Patent 13/061,585

Theses

  1. Maeda, G. (2013). “Learning and Reacting with Inaccurate Prediction: Applications to Autonomous Excavation”, Ph.D Thesis, The University of Sydney. [pdf][BibTeX]
  2. Maeda, G. (2007). “Practical Control of Leadscrew Mechanism for Ultra-Precision Positioning”, Master Thesis, Tokyo Institute of Technology. [pdf][BibTeX]