8 papers
Tracing Back Error Sources to Explain and Mitigate Pose Estimation Failures
Loris Schneider, Yitian Shi, Rosa Wolf +3
Robust estimation of object poses in robotic manipulation is often addressed using foundational general estimators, that aim to handle diverse error sources naively within a single…
Human-Interpretable Uncertainty Explanations for Point Cloud Registration
Johannes A. Gaus, Loris Schneider, Yitian Shi +3
In this paper, we address the point cloud registration problem, where well-known methods like ICP fail under uncertainty arising from sensor noise, pose-estimation errors, and part…
HOGraspFlow: Taxonomy-Aware Hand-Object Retargeting for Multi-Modal SE(3) Grasp Generation
Yitian Shi, Zicheng Guo, Rosa Wolf +2
We propose Hand-Object\emph{(HO)GraspFlow}, an affordance-centric approach that retargets a single RGB with hand-object interaction (HOI) into multi-modal executable parallel jaw g…
Interactive Imitation Learning for Dexterous Robotic Manipulation: Challenges and Perspectives -- A Survey
Edgar Welte, Rania Rayyes
Dexterous manipulation is a crucial yet highly complex challenge in humanoid robotics, demanding precise, adaptable, and sample-efficient learning methods. As humanoid robots are u…
Diffusion Models for Robotic Manipulation: A Survey
Rosa Wolf, Yitian Shi, Sheng Liu +1
Diffusion generative models have demonstrated remarkable success in visual domains such as image and video generation. They have also recently emerged as a promising approach in ro…
VISO-Grasp: Vision-Language Informed Spatial Object-centric 6-DoF Active View Planning and Grasping in Clutter and Invisibility
Yitian Shi, Di Wen, Guanqi Chen +5
We propose VISO-Grasp, a novel vision-language-informed system designed to systematically address visibility constraints for grasping in severely occluded environments. By leveragi…