publications | CI Robot Learning Lab

2025

Discrete Codebook World Models for Continuous Control

Aidan Scannell, Mohammadreza Nakhaeinezhadfard, Kalle Kujanpää, and 4 more authors

In The Thirteenth International Conference on Learning Representations, 2025

@inproceedings{scannelldiscrete,
  title = {Discrete Codebook World Models for Continuous Control},
  author = {Scannell, Aidan and Nakhaeinezhadfard, Mohammadreza and Kujanp{\"a}{\"a}, Kalle and Zhao, Yi and Luck, Kevin Sebastian and Solin, Arno and Pajarinen, Joni},
  booktitle = {The Thirteenth International Conference on Learning Representations},
  year = {2025},
}

2024

Accelerating Laboratory Automation Through Robot Skill Learning For Sample Scraping

Gabriella Pizzuto, Hetong Wang, Hatem Fakhruldeen, and 3 more authors

IEEE CASE 2024, 2024

Bib PDF

@article{pizzuto2024accelerating,
  title = {Accelerating Laboratory Automation Through Robot Skill Learning For Sample Scraping},
  author = {Pizzuto, Gabriella and Wang, Hetong and Fakhruldeen, Hatem and Peng, Bei and Luck, Kevin Sebastian and Cooper, Andrew I},
  journal = {IEEE CASE 2024},
  year = {2024},
}

Springer

Co-imagination of Behaviour and Morphology of Agents

Maria Sliacka, Michael Mistry, Roberto Calandra, and 2 more authors

In Machine Learning, Optimization, and Data Science, 2024

Bib PDF

@inproceedings{10.1007/978-3-031-53969-5_24,
  author = {Sliacka, Maria and Mistry, Michael and Calandra, Roberto and Kyrki, Ville and Luck, Kevin Sebastian},
  editor = {Nicosia, Giuseppe and Ojha, Varun and La Malfa, Emanuele and La Malfa, Gabriele and Pardalos, Panos M. and Umeton, Renato},
  title = {Co-imagination of Behaviour and Morphology of Agents},
  booktitle = {Machine Learning, Optimization, and Data Science},
  year = {2024},
  publisher = {Springer Nature Switzerland},
  address = {Cham},
  pages = {318--332},
  isbn = {978-3-031-53969-5},
}

Investigation into Bio-inspired Snake Robot Designs with Co-Adaptation of Morphology and Behaviour

Riccardo Pretto, Sylvia Cressmann, Shivam Chaubey, and 3 more authors

In 40th Anniversary of the IEEE International Conference on Robotics and Automation (ICRA@40), 2024

Bib PDF

@inproceedings{pretto_snake,
  author = {Pretto, Riccardo and Cressmann, Sylvia and Chaubey, Shivam and Jansen, Michael Andrew and Kyrki, Ville and Luck, Kevin Sebastian},
  title = {Investigation into Bio-inspired Snake Robot Designs with
  Co-Adaptation of Morphology and Behaviour},
  booktitle = {40th Anniversary of the IEEE International Conference on Robotics and Automation (ICRA@40)},
  year = {2024},
  publisher = {Abstract},
}

Following Ancestral Footsteps: Co-Designing Morphology and Behaviour with Self-Imitation Learning

Sergio Hernandez-Gutierrez, Ville Kyrki, and Kevin Sebastian Luck

In Seventeenth European Workshop on Reinforcement Learning, 2024

Bib PDF

@inproceedings{hernandezfollowing,
  title = {Following Ancestral Footsteps: Co-Designing Morphology and Behaviour with Self-Imitation Learning},
  author = {Hernandez-Gutierrez, Sergio and Kyrki, Ville and Luck, Kevin Sebastian},
  booktitle = {Seventeenth European Workshop on Reinforcement Learning},
  year = {2024},
}

CoRL

Learning Transparent Reward Models via Unsupervised Feature Selection

Daulet Baimukashev, Gokhan Alcan, Kevin Sebastian Luck, and 1 more author

In 8th Annual Conference on Robot Learning, 2024

Bib PDF

@inproceedings{baimukashevlearning,
  title = {Learning Transparent Reward Models via Unsupervised Feature Selection},
  author = {Baimukashev, Daulet and Alcan, Gokhan and Luck, Kevin Sebastian and Kyrki, Ville},
  booktitle = {8th Annual Conference on Robot Learning},
  year = {2024}
}

Policy Space Response Oracles: A Survey

Ariyan Bighashdel, Yongzhao Wang, Stephen McAleer, and 2 more authors

In Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, IJCAI-24, Aug 2024

Survey Track

DOI
Off-Policy Action Anticipation in Multi-Agent Reinforcement Learning

Ariyan Bighashdel, Daan Geus, Pavol Jancura, and 1 more author

Journal of Machine Learning Research, Aug 2024

2023

NeurIPS

Conditional Mutual Information for Disentangled Representations in Reinforcement Learning

Mhairi Dunion, Trevor McInroe, Kevin Sebastian Luck, and 2 more authors

In Thirty-seventh Conference on Neural Information Processing Systems, Aug 2023

Bib PDF

@inproceedings{dunion2023conditional,
  title = {Conditional Mutual Information for Disentangled Representations in Reinforcement Learning},
  author = {Dunion, Mhairi and McInroe, Trevor and Luck, Kevin Sebastian and Hanna, Josiah P. and Albrecht, Stefano V},
  booktitle = {Thirty-seventh Conference on Neural Information Processing Systems},
  year = {2023},
  url = {https://openreview.net/forum?id=EmYWJsyad4},
}

NeurIPS

Practical Equivariances via Relational Conditional Neural Processes

Daolang Huang, Manuel Haussmann, Ulpu Remes, and 5 more authors

In Thirty-seventh Conference on Neural Information Processing Systems, Aug 2023

Bib PDF

@inproceedings{huang2023practical,
  title = {Practical Equivariances via Relational Conditional Neural Processes},
  author = {Huang, Daolang and Haussmann, Manuel and Remes, Ulpu and John, S. T. and Clart{\'e}, Gr{\'e}goire and Luck, Kevin Sebastian and Kaski, Samuel and Acerbi, Luigi},
  booktitle = {Thirty-seventh Conference on Neural Information Processing Systems},
  year = {2023},
  url = {https://openreview.net/forum?id=xax5eWeObb},
}

AAAI

Co-imitation: learning design and behaviour by imitation

Chang Rajani, Karol Arndt, David Blanco-Mulero, and 2 more authors

In Proceedings of the AAAI Conference on Artificial Intelligence, Aug 2023

Bib PDF

@inproceedings{rajani2023co,
  title = {Co-imitation: learning design and behaviour by imitation},
  author = {Rajani, Chang and Arndt, Karol and Blanco-Mulero, David and Luck, Kevin Sebastian and Kyrki, Ville},
  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
  volume = {37},
  number = {5},
  pages = {6200--6208},
  year = {2023},
}

Model-free inverse reinforcement learning with multi-intention, unlabeled, and overlapping demonstrations

Ariyan Bighashdel, Pavol Jancura, and Gijs Dubbelman

Machine Learning, Aug 2023
Continual Pedestrian Trajectory Learning With Social Generative Replay

Ya Wu, Ariyan Bighashdel, Guang Chen, and 2 more authors

IEEE Robotics and Automation Letters, Aug 2023

DOI

2022

Which language evolves between heterogeneous agents?-communicating movement instructions with widely different time scopes

Marie Ossenkopf, Kevin Sebastian Luck, and Kory Wallace Mathewson

In Emergent Communication Workshop at ICLR 2022, Aug 2022

Bib PDF

@inproceedings{ossenkopf2022language,
  title = {Which language evolves between heterogeneous agents?-communicating movement instructions with widely different time scopes},
  author = {Ossenkopf, Marie and Luck, Kevin Sebastian and Mathewson, Kory Wallace},
  booktitle = {Emergent Communication Workshop at ICLR 2022},
  year = {2022},
}

RA-L

Residual learning from demonstration: Adapting dmps for contact-rich manipulation

Todor Davchev, Kevin Sebastian Luck, Michael Burke, and 3 more authors

IEEE Robotics and Automation Letters, Aug 2022

Bib PDF

@article{davchev2022residual,
  title = {Residual learning from demonstration: Adapting dmps for contact-rich manipulation},
  author = {Davchev, Todor and Luck, Kevin Sebastian and Burke, Michael and Meier, Franziska and Schaal, Stefan and Ramamoorthy, Subramanian},
  journal = {IEEE Robotics and Automation Letters},
  volume = {7},
  number = {2},
  pages = {4488--4495},
  year = {2022},
  publisher = {IEEE},
}

ICLR

Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning

Mhairi Dunion, Trevor McInroe, Kevin Sebastian Luck, and 2 more authors

In The Eleventh International Conference on Learning Representations, Aug 2022

Bib PDF

@inproceedings{dunion2022temporal,
  title = {Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning},
  author = {Dunion, Mhairi and McInroe, Trevor and Luck, Kevin Sebastian and Hanna, Josiah P and Albrecht, Stefano V},
  booktitle = {The Eleventh International Conference on Learning Representations},
  year = {2022},
}

ICML

SpaceMAP: Visualizing High-Dimensional Data by Space Expansion

Xinrui Zu, and Qian Tao

In Proceedings of the 39th International Conference on Machine Learning, 17–23 jul 2022

Bib PDF

@inproceedings{pmlr-v162-zu22a,
  title = {{S}pace{MAP}: Visualizing High-Dimensional Data by Space Expansion},
  author = {Zu, Xinrui and Tao, Qian},
  booktitle = {Proceedings of the 39th International Conference on Machine Learning},
  pages = {27707--27723},
  year = {2022},
  editor = {Chaudhuri, Kamalika and Jegelka, Stefanie and Song, Le and Szepesvari, Csaba and Niu, Gang and Sabato, Sivan},
  volume = {162},
  series = {Proceedings of Machine Learning Research},
  month = {17--23 Jul},
  publisher = {PMLR},
  url = {https://proceedings.mlr.press/v162/zu22a.html},
}

2021

What robot do i need? Fast co-adaptation of morphology and control using graph neural networks

Kevin Sebastian Luck, Roberto Calandra, and Michael Mistry

arXiv preprint arXiv:2111.02371, 17–23 jul 2021

Bib PDF

@article{luck2021robot,
  title = {What robot do i need? Fast co-adaptation of morphology and control using graph neural networks},
  author = {Luck, Kevin Sebastian and Calandra, Roberto and Mistry, Michael},
  journal = {arXiv preprint arXiv:2111.02371},
  year = {2021},
}

2020

CoRL
Data-efficient Co-Adaptation of Morphology and Behaviour with Deep Reinforcement Learning

Kevin Sebastian Luck, Heni Ben Amor, and Roberto Calandra

In Proceedings of the Conference on Robot Learning, 30 oct–01 nov 2020

Abs Bib PDF

Humans and animals are capable of quickly learning new behaviours to solve new tasks. Yet, we often forget that they also rely on a highly specialized morphology that co-adapted with motor control throughout thousands of years. Although compelling, the idea of co-adapting morphology and behaviours in robots is often unfeasible because of the long manufacturing times, and the need to redesign an appropriate controller for each morphology. In this paper, we propose a novel approach to automatically and efficiently co-adapt a robot morphology and its controller. Our approach is based on recent advances in deep reinforcement learning, and specifically the soft actor critic algorithm. Key to our approach is the possibility of leveraging previously tested morphologies and behaviors to estimate the performance of new candidate morphologies. As such, we can make full use of the information available for making more informed decisions, with the ultimate goal of achieving a more data-efficient co-adaptation (i.e., reducing the number of morphologies and behaviors tested). Simulated experiments show that our approach requires drastically less design prototypes to find good morphology-behaviour combinations, making this method particularly suitable for future co-adaptation of robot designs in the real world.
@inproceedings{pmlr-v100-luck20a, title = {Data-efficient Co-Adaptation of Morphology and Behaviour with Deep Reinforcement Learning}, author = {Luck, Kevin Sebastian and Amor, Heni Ben and Calandra, Roberto}, booktitle = {Proceedings of the Conference on Robot Learning}, pages = {854--869}, year = {2020}, editor = {Kaelbling, Leslie Pack and Kragic, Danica and Sugiura, Komei}, volume = {100}, series = {Proceedings of Machine Learning Research}, month = {30 Oct--01 Nov}, publisher = {PMLR}, url = {https://proceedings.mlr.press/v100/luck20a.html}, }

2019

IROS

Improved exploration through latent trajectory optimization in deep deterministic policy gradient

Kevin Sebastian Luck, Mel Vecerik, Simon Stepputtis, and 2 more authors

In 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 30 oct–01 nov 2019

Bib PDF

@inproceedings{luck2019improved,
  title = {Improved exploration through latent trajectory optimization in deep deterministic policy gradient},
  author = {Luck, Kevin Sebastian and Vecerik, Mel and Stepputtis, Simon and Amor, Heni Ben and Scholz, Jonathan},
  booktitle = {2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  pages = {3704--3711},
  year = {2019},
  organization = {IEEE},
}

2017

Springer

Bio-inspired robot design considering load-bearing and kinematic ontogeny of chelonioidea sea turtles

Andrew Jansen, Kevin Sebastian Luck, Joseph Campbell, and 2 more authors

In Biomimetic and Biohybrid Systems: 6th International Conference, Living Machines 2017, Stanford, CA, USA, July 26–28, 2017, Proceedings 6, 30 oct–01 nov 2017

Bib PDF

@inproceedings{jansen2017bio,
  title = {Bio-inspired robot design considering load-bearing and kinematic ontogeny of chelonioidea sea turtles},
  author = {Jansen, Andrew and Luck, Kevin Sebastian and Campbell, Joseph and Amor, Heni Ben and Aukes, Daniel M},
  booktitle = {Biomimetic and Biohybrid Systems: 6th International Conference, Living Machines 2017, Stanford, CA, USA, July 26--28, 2017, Proceedings 6},
  pages = {216--229},
  year = {2017},
  organization = {Springer},
}

R:SS

From the Lab to the Desert: Fast Prototyping and Learning of Robot Locomotion

Kevin Sebastian Luck, Joseph Campbell, Michael Jansen, and 2 more authors

In Proceedings of Robotics: Science and Systems, Jul 2017

DOI Bib PDF

@inproceedings{Luck-RSS-17,
  author = {Luck, Kevin Sebastian and Campbell, Joseph and Jansen, Michael and Aukes, Daniel and Amor, Heni Ben},
  title = {From the Lab to the Desert: Fast Prototyping and Learning of Robot Locomotion},
  booktitle = {Proceedings of Robotics: Science and Systems},
  year = {2017},
  address = {Cambridge, Massachusetts},
  month = jul,
  doi = {10.15607/RSS.2017.XIII.075},
}

IROS

Extracting bimanual synergies with reinforcement learning

Kevin Sebastian Luck, and Heni Ben Amor

In 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Jul 2017

Bib PDF

@inproceedings{luck2017extracting,
  title = {Extracting bimanual synergies with reinforcement learning},
  author = {Luck, Kevin Sebastian and Amor, Heni Ben},
  booktitle = {2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  pages = {4805--4812},
  year = {2017},
  organization = {IEEE},
}

2016

AAAI

Sparse latent space policy search

Kevin Sebastian Luck, Joni Pajarinen, Erik Berger, and 2 more authors

In Proceedings of the AAAI Conference on Artificial Intelligence, Jul 2016

Bib PDF

@inproceedings{luck2016sparse,
  title = {Sparse latent space policy search},
  author = {Luck, Kevin Sebastian and Pajarinen, Joni and Berger, Erik and Kyrki, Ville and Amor, Heni Ben},
  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
  volume = {30},
  number = {1},
  year = {2016},
}

2014

IROS

Latent space policy search for robotics

Kevin Sebastian Luck, Gerhard Neumann, Erik Berger, and 2 more authors

In 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, Jul 2014

Bib PDF

@inproceedings{luck2014latent,
  title = {Latent space policy search for robotics},
  author = {Luck, Kevin Sebastian and Neumann, Gerhard and Berger, Erik and Peters, Jan and Amor, Heni Ben},
  booktitle = {2014 IEEE/RSJ International Conference on Intelligent Robots and Systems},
  pages = {1434--1440},
  year = {2014},
  organization = {IEEE},
}