6 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
A novel robotic end-effector is introduced for pick-and-release of several fabric parts used for producing underwear. One of the main operations in a factory for sewing cloth products is to pick up fabric parts, provide them to a sewing machine, and sew them together. In the case of underwear, thin
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
This paper proposes a novel visual Learning from Demonstration (LfD) system that teaches robots to learn tasks in which an object is put into another object, stacked, or transported by a tool. In such tasks, observation targets become invisible owing to occlusion or frame-out. The proposed “Visual H…
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
We propose a method for a robot to manipulate an unknown door based on a single user instruction. The primary contributions of this paper are (i) to reduce the user instruction to a single click and (ii) to develop an efficient method to estimate an appropriate shape and manipulation model for a tar…