Ville Kyrki

Ville Kyrki

T410 Dept. Electrical Engineering and Automation

Ville Kyrki is a Full Professor at Aalto University School of Electrical Engineering. He joined Aalto University as an Associate Professor in 2012. He serves as the head of the Intelligent Robotics research group.

His research interests lie mainly in intelligent robotic systems with a particular emphasis on developing methods and systems that cope with imperfect knowledge and uncertain senses. His published research covers feature extraction and tracking in computer vision, visual servoing, tactile sensing, robotic grasping and manipulation, sensor fusion, planning under uncertainty, and machine learning related to the previous. His research has been published in numerous forums in the area, including IEEE Transactions on Robotics, International Journal of Robotics Research, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Haptics, and IEEE Transactions on Image Processing.

Full researcher profile

Contact information

Postal address
Maarintie 8 02150 Espoo Finland
Phone number

Research groups

  • Intelligent Robotics


LSVL: Large-scale season-invariant visual localization for UAVs

Jouko Kinnari, Riccardo Renzulli, Francesco Verdoja, Ville Kyrki 2023 Robotics and Autonomous Systems

POMDP Planning Under Object Composition Uncertainty

Joni Pajarinen, Jens Lundell, Ville Kyrki 2023 IEEE Transactions on Robotics

DROPO: Sim-to-real transfer with offline domain randomization

Gabriele Tiboni, Karol Arndt, Ville Kyrki 2023 Robotics and Autonomous Systems

Training and Evaluation of Deep Policies Using Reinforcement Learning and Generative Models

Ali Ghadirzadeh, Petra Poklukar, Karol Arndt, Chelsea Finn, Ville Kyrki, Danica Kragic, Mårten Björkman 2022 Journal of Machine Learning Research

Learning Visual Feedback Control for Dynamic Cloth Folding

Julius Hietala, David Blanco Mulero, Gökhan Alcan, Ville Kyrki 2022 Proceedings of the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2022

Deformation-Aware Data-Driven Grasp Synthesis

Tran Nguyen Le, Jens Lundell, Fares Abu-Dakka, Ville Kyrki 2022 IEEE Robotics and Automation Letters

Few-shot model-based adaptation in noisy conditions

Karol Arndt, Ali Ghadirzadeh, Murtaza Hazara, Ville Kyrki 2021 IEEE Robotics and Automation Letters

DDGC: Generative Deep Dexterous Grasping in Clutter

Jens Lundell, Francesco Verdoja, Ville Kyrki 2021 IEEE Robotics and Automation Letters

Imitation learning-based framework for learning 6-D linear compliant motions

Markku Suomalainen, Fares Abu-Dakka, Ville Kyrki 2021 Autonomous Robots

Meta Reinforcement Learning for Sim-to-real Domain Adaptation

Karol Arndt, Murtaza Hazara, Ali Ghadirzadeh, Ville Kyrki 2020 Proceedings of the IEEE Conference on Robotics and Automation, ICRA 2020