Environmentally Adaptive Control Including Variance Minimization Using Stochastic Predictive Network with Parametric Bias: Application to Mobile Robots
Kento Kawaharazuka,Koki Shinjo,Yoichiro Kawamura,Kei Okada,Masayuki Inaba,Kento Kawaharazuka,Koki Shinjo,Yoichiro Kawamura,Kei Okada,Masayuki Inaba
In this study, we propose a predictive model composed of a recurrent neural network including parametric bias and stochastic elements, and an environmentally adaptive robot control method including variance minimization using the model. Robots which have flexible bodies or whose states can only be partially observed are difficult to modelize, and their predictive models often have stochastic behav...
