robot motion generation
  We develop novel control schemes to generate expressive robot motion and solve optimal control and inverse optimal control using latent space of machine learning techniques. Our control methods are tested on a wide range of robots and can apply in many use cases.
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.

S. Shimizu, K. Ayusawa, G. Venture, Motion Synthesis Using Low-dimensional Feature Space and Its Application to Inverse Optimal Control, ROMANSY, Sapporo, Japan, 20-24 September, 2020.

A. Claret, G. Venture, L. Basanez, Exploring the robot kinematic redundancy for emotion conveyance to humans as a lower priority task , Int. J. of Social Robotics, Vol. 9, No. 2, pp. 277-292, 2017. DOI 10.1007/s12369-016-0387-2 Springer




copyright Gentiane Venture 2009