Kansei adaptative robot control
  We develop novel control schemes that enable robots to be expressive through their movements. We base our research on concepts from Kansei enginering and control theory such as null-space control and optimal control. We also use machine learning techniques.
related publications

S. Ishida, T. Harada, P. Carreno, D. Kulic, G. Venture, Human Motion Imitation using Optimal Control with Time‐Varying Weights, Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, September 27th - October 1st, 2021.

L. E. Coronado Zuniga, G. Venture, N. Yamanobe, Applying Kansei/Affective Engineering Methodologies in the Design of Social and Service Robots: A Systematic Review, Int. J. of Social Robotics, 2020. DOI: 10.1007/s12369-020-00709-x

T. Izui, G. Venture, Predictive models of robot user's impression: A study on visual medium and mechanical noise, Int. J. of Social Robotics, 2019. DOI: 10.1007/s12369-019-00601-3

G. Venture, D. Kulic, Robot expressive motions: a survey of generation and evaluation methods, ACM Transactions on Human-Robot Interaction, Vol. 8, No 4, a20, 2019. 10.1145/3344286

S. Kato, N. Yamanobe, G. Venture, E. Yoshida, G. Ganesh, The where of Handovers by Human: Effect of partner characteristics, distance and visual feedback, PLoSONE, 2019. DOI  

L. Rincon Ardila, E. Coronado, H. Hendra, J. Phan, Z. Izzati Binti Zainalkefli, G. Venture, Expressive States with a Robot arm using Adaptive Fuzzy and Robust Predictive Controllers, Int. J. of Mechanical Engineering and Robotics Research, Vol. 8, No. 2, pp. 207-219, 2019. Open Access




copyright Gentiane Venture 2009