5 accepted papers
Supervised behavioral cloning using robot visual-action data has been widely investigated in robot manipulation. However, these methods typically require simultaneous acquisition of visual and action data, which makes them difficult to utilize unpaired visual-action datasets: e.g. videos on Internet
Bimanual dexterous manipulation remains a significant challenge in robotics due to the high DoFs of each hand and their coordination. Existing single-hand manipulation techniques often leverage human demonstrations to guide RL methods but fail to generalize to complex bimanual tasks involving multip
Vision and touch are the most commonly used senses in human manipulation. While leveraging human manipulation videos for robotic task pretraining has shown promise in prior works, it is limited to image and language modalities and deployment to simple parallel grippers. In this paper, aiming to addr…
Recent works on the pretraining for robot manipulation have demonstrated that representations learning from large human manipulation data can generalize well to new manipulation tasks and environments. However, these approaches mainly focus on human vision or natural language, neglecting tactile fee…
Robotic dexterous grasping is a challenging problem due to the high degree of freedom (DoF) and complex contacts of multi-fingered robotic hands. Existing deep re-inforcement learning (DRL) based methods leverage human demonstrations to reduce sample complexity due to the high dimensional action spa…