Welcome to LiRA, where we focus on developing embodied AI agents. Unlike traditional passive AI systems, we specialize in crafting active AI agents capable of understanding and dynamically interacting with the physical world, much like humans do. Our goal extends to the seamless coexistence and collaboration between humans and robots, envisioning a future where these entities work harmoniously together. Drawing from an interdisciplinary toolkit, our research leverages methodologies from reinforcement learning, machine learning, deep learning, optimization, and probabilistic inference.

news

Sep 22, 2025	Asst. Prof. Özgür S. Öğüz was one of the speakers at the ROMER-3R Robotic Research Retreat held at ODTÜ (METU) on September 22, 2025.
Jun 15, 2024	Our preprint (on Deep Reinforcement Learning) is out CUER: Corrected Uniform Experience Replay for Off-Policy Continuous Deep Reinforcement Learning Algorithms - [pdf].

MO-SeGMan: Rearrangement Planning Framework for Multi Objective Sequential and Guided Manipulation in Constrained Environments

Cankut Bora Tuncer , Marc Toussaint , and Ozgur S Oguz

arXiv preprint arXiv:2511.01476, 2025

Bib

@article{25-tuncer2025-Arxiv,
  title = {MO-SeGMan: Rearrangement Planning Framework for Multi Objective Sequential and Guided Manipulation in Constrained Environments},
  author = {Tuncer, Cankut Bora and Toussaint, Marc and Oguz, Ozgur S},
  journal = {arXiv preprint arXiv:2511.01476},
  year = {2025},
}

SeGMan: Sequential and Guided Manipulation Planner for Robust Planning in 2D Constrained Environments

Cankut Bora Tuncer , Dilruba Sultan Haliloglu , and Ozgur S Oguz

2025

Bib

@article{25-tuncer-IROS,
  title = {SeGMan: Sequential and Guided Manipulation Planner for Robust Planning in 2D Constrained Environments},
  author = {Tuncer, Cankut Bora and Haliloglu, Dilruba Sultan and Oguz, Ozgur S},
  booktitle = {2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year = {2025},
  organization = {IEEE},
}

Way-Tu: A Framework for Tool Selection and Manipulation Using Waypoint Representations

Ece Kunduracioglu , and Ozgur S Oguz

In Dexterous Manipulation: Learning and Control with Diverse Modalities , 2025

Bib

@inproceedings{25-kunduracioglu-CoRLWorkshop,
  title = {Way-Tu: A Framework for Tool Selection and Manipulation Using Waypoint Representations},
  year = {2025},
  author = {Kunduracioglu, Ece and Oguz, Ozgur S},
  booktitle = {Dexterous Manipulation: Learning and Control with Diverse Modalities},
}

H-MaP: An Iterative and Hybrid Sequential Manipulation Planner

Berk Cicek , Arda Sarp Yenicesu , Cankut Bora Tuncer , and 2 more authors

IEEE Robotics and Automation Letters, 2025

Bib

@article{25-cicek-RA-L,
  title = {H-MaP: An Iterative and Hybrid Sequential Manipulation Planner},
  author = {Cicek, Berk and Yenicesu, Arda Sarp and Tuncer, Cankut Bora and Demiray, Kutay and Oguz, Ozgur S},
  journal = {IEEE Robotics and Automation Letters},
  year = {2025},
  publisher = {IEEE},
}

CUER: Corrected Uniform Experience Replay for Off-Policy Continuous Deep Reinforcement Learning Algorithms

Arda Sarp Yenicesu , Furkan B. Mutlu , Suleyman S. Kozat , and 1 more author

2024

arXiv Bib

@misc{24-yenicesu-Arxiv,
  title = {CUER: Corrected Uniform Experience Replay for Off-Policy Continuous Deep Reinforcement Learning Algorithms},
  author = {Yenicesu, Arda Sarp and Mutlu, Furkan B. and Kozat, Suleyman S. and Oguz, Ozgur S.},
  year = {2024},
}

Bilkent University
Department of Computer Engineering
Cankaya 06800 Ankara

Learning for Intelligent Robotic Agents

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