Ville Kyrki

Ville Kyrki

Professori (Associate professor)
T410 Dept. Electrical Engineering and Automation
Professori (Associate professor)

Ville Kyrki joined School of Electrical Engineering at 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
https://research.aalto.fi/...

Yhteystiedot

Sähköposti
[email protected]
Postiosoite
Maarintie 8 02150 Espoo Finland
Puhelinnumero
+358504082035

Tutkimusryhmät

  • Intelligent Robotics

Julkaisut

A Safety-Critical Decision-Making and Control Framework Combining Machine-Learning-Based and Rule-Based Algorithms

Andrei Aksjonov, Ville Kyrki 2023 SAE International Journal of Vehicle Dynamics, Stability, and NVH

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

Co-Imitation: Learning Design and Behaviour by Imitation

Chang Rajani, David Blanco Mulero, Karol Arndt, Kevin Luck, Ville Kyrki 2023 AAAI-23 Technical Tracks 5

Learning stable robotic skills on Riemannian manifolds

Matteo Saveriano, Fares J. Abu-Dakka, Ville Kyrki 2023 Robotics and Autonomous Systems

Autoencoding Slow Representations for Semi-supervised Data-Efficient Regression

Oliver Struckmeier, Kshitij Tiwari, Ville Kyrki 2023 Machine Learning

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

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

Online vs. Offline Adaptive Domain Randomization Benchmark

Gabriele Tiboni, Karol Arndt, Giuseppe Averta, Ville Kyrki, Tatiana Tommasi 2023 Human-Friendly Robotics 2022 - HFR

Bidding a Battery on Electricity Markets and Minimizing Battery Aging Costs: A Reinforcement Learning Approach

Harri Aaltonen, Seppo Sierla, Ville Kyrki, Mahdi Pourakbari‐kasmaei, Valeriy Vyatkin 2022 Energies