Visual Task Progress Estimation with Appearance Invariant Embeddings for Robot Control and Planning
Guilherme Maeda,Joni Väätäinen,Hironori Yoshida,Guilherme Maeda,Joni Väätäinen,Hironori Yoshida
One of the challenges of full autonomy is to have robots capable of manipulating its current environment to achieve another environment configuration. This paper is a step towards this challenge, focusing on the visual understanding of the task. Our approach trains a deep neural network to represent images as measurable features that are useful to estimate the progress (or phase) of a task. The tr...
