Physically Consistent Preferential Bayesian Optimization for Food Arrangement

no code implementations • 21 Sep 2022 • Yuhwan Kwon, Yoshihisa Tsurumine, Takeshi Shimmura, Sadao Kawamura, Takamitsu Matsubara

To cope with this problem, we propose Physically Consistent Preferential Bayesian Optimization (PCPBO) as a method that obtains physically feasible and preferred arrangements that satisfy domain rules.

Bayesian Optimization

Randomized-to-Canonical Model Predictive Control for Real-world Visual Robotic Manipulation

no code implementations • 5 Jul 2022 • Tomoya Yamanokuchi, Yuhwan Kwon, Yoshihisa Tsurumine, Eiji Uchibe, Jun Morimoto, Takamitsu Matsubara

However, such works are limited to one-shot transfer, where real-world data must be collected once to perform the sim-to-real transfer, which remains a significant human effort in transferring the models learned in simulations to new domains in the real world.

Model Predictive Control