8 papers
DDBot: Differentiable Physics-based Digging Robot for Unknown Granular Materials
Xintong Yang, Minglun Wei, Yu-Kun Lai +1
Automating the manipulation of granular materials poses significant challenges due to complex contact dynamics, unpredictable material properties, and intricate system states. Exis…
Training-Free Video Editing via Optical Flow-Enhanced Score Distillation
Lianghan Zhu, Yanqi Bao, Jing Huo +4
The rapid advancement in visual generation, particularly the emergence of pre-trained text-to-image and text-to-video models, has catalyzed growing interest in training-free video…
SEA: Semantic Map Prediction for Active Exploration of Uncertain Areas
Hongyu Ding, Xinyue Liang, Yudong Fang +7
In this paper, we propose SEA, a novel approach for active robot exploration through semantic map prediction and a reinforcement learning-based hierarchical exploration policy. Unl…
Differentiable Skill Optimisation for Powder Manipulation in Laboratory Automation
Minglun Wei, Xintong Yang, Yu-Kun Lai +1
Robotic automation is accelerating scientific discovery by reducing manual effort in laboratory workflows. However, precise manipulation of powders remains challenging, particularl…
A Physics-informed Demonstration-guided Learning Framework for Granular Material Manipulation
Minglun Wei, Xintong Yang, Yu-Kun Lai +2
Due to the complex physical properties of granular materials, research on robot learning for manipulating such materials predominantly either disregards the consideration of their…
MirrorSAM2: Segment Mirror in Videos with Depth Perception
Mingchen Xu, Yukun Lai, Ze Ji +1
This paper presents MirrorSAM2, the first framework that adapts Segment Anything Model 2 (SAM2) to the task of RGB-D video mirror segmentation. MirrorSAM2 addresses key challenges…