3 accepted papers
We propose a novel system for action sequence planning based on a combination of affordance recognition and a neural forward model predicting the effects of affordance execution. By performing affordance recognition on predicted futures, we avoid reliance on explicit affordance effect definitions fo
We consider the problem of deformable object manipulation with variable goal states and mid-manipulation disruptions. We propose an approach that integrates online shape estimation, prediction of shape transitions, and mid-manipulation trajectory correction. All functionalities are implemented using
In this letter, we present a motion planning method for automatic operation of cloth products. The problem setting we adopt here is that the current shape state of a cloth product and the shape state of the goal are given. It is necessary to decide where and what kind of manipulation is to be applie