A regression problem is one where the goal is to predict a single numeric value. For example, you might want to predict the price of a house based on its square footage, age, number of bedrooms and ...
This research from Keio University leverages Gaussian process regression, enabling robots to intuitively adjust grip based on ...
Despite rapid robotic automation advancements, most systems struggle to adapt their pre-trained movements to dynamic ...
We propose a nested Gaussian process (nGP) as a locally adaptive prior for Bayesian nonparametric regression. Specified through a set of stochastic differential equations (SDEs), the nGP imposes a ...
Researchers develop an adaptive motion system that allows robots to generate human-like movements with minimal data ...