The motivation behind our work is to review and analyze the most relevant studies on deep
reinforcement learning-based object manipulation. Various studies are examined through a …

Abstract Generative Adversarial Imitation Learning (GAIL) can learn policies without
explicitly defining the reward function from demonstrations. GAIL has the potential to learn …

We consider the problem of deformable object manipulation with variable goal states and
mid-manipulation disruptions. We propose an approach that integrates online shape …

In this paper, we propose a manipulation planning method for cable wiring in the assembly
of electric appliances etc. We address a scenario where a robot grasps a connector attached …

Cloth manipulation is common in both housework and manufacturing. However, robotic cloth
manipulation remains challenging, especially for less controlled and open-goal settings. We …

Deformable object manipulation has been considered a challenging task for robots for its
complex dynamics and the infinite dimensional configuration space. Fabric unfolding …

Featured Application Learned robotic manipulation skills for clothing on a low-cost robot by
building a DIY smart textile and using a single CPU core. Abstract Deformable objects such …

We propose a novel robotic system that combines both a reliable programming-based
approach and a highly generalizable learning-based approach. How to design and …

Food preparation is hard to automate on general-purpose robot hardware. This work
focuses on acquisition of cutting manipulations for food preparation. We construct a physical …

In this work, we propose a novel strategy to ensure infants, who inadvertently displace their
quilts during sleep, are promptly and accurately re-covered. Our approach is formulated into …