DIPN: Deep Interaction Prediction Network with Application to Clutter Removal
Baichuan Huang Shuai D. Han Abdeslam Boularias Jingjin Yu Baichuan Huang Shuai D. Han Abdeslam Boularias Jingjin Yu
We propose a Deep Interaction Prediction Network (DIPN) for learning to predict complex interactions that ensue as a robot end-effector pushes multiple objects, whose physical properties, including size, shape, mass, and friction coefficients may be unknown a priori. DIPN "imagines" the effect of a push action and generates an accurate synthetic image of the predicted outcome. DIPN is shown to be ...