7 citations · 8 across the 6 of their papers we have counts for
6 papers
Point Cloud Models Improve Visual Robustness in Robotic Learners
Skand Peri, Iain Lee, Chanho Kim +3
Visual control policies can encounter significant performance degradation when visual conditions like lighting or camera position differ from those seen during training -- often ex…
V-PRISM: Probabilistic Mapping of Unknown Tabletop Scenes
Herbert Wright, Weiming Zhi, Matthew Johnson-Roberson +1
The ability to construct concise scene representations from sensor input is central to the field of robotics. This paper addresses the problem of robustly creating a 3D representat…
Pick and Place Planning is Better than Pick Planning then Place Planning
Mohanraj Devendran Shanthi, Tucker Hermans
Robotic pick and place stands at the heart of autonomous manipulation. When conducted in cluttered or complex environments robots must jointly reason about the selected grasp and d…
DefGoalNet: Contextual Goal Learning from Demonstrations For Deformable Object Manipulation
Bao Thach, Tanner Watts, Shing-Hei Ho +2
Shape servoing, a robotic task dedicated to controlling objects to desired goal shapes, is a promising approach to deformable object manipulation. An issue arises, however, with th…
DefGraspNets: Grasp Planning on 3D Fields with Graph Neural Nets
Isabella Huang, Yashraj Narang, Ruzena Bajcsy +3
Robotic grasping of 3D deformable objects is critical for real-world applications such as food handling and robotic surgery. Unlike rigid and articulated objects, 3D deformable obj…
Occlusion-Robust Multi-Sensory Posture Estimation in Physical Human-Robot Interaction
Amir Yazdani, Roya Sabbagh Novin, Andrew Merryweather +1
3D posture estimation is important in analyzing and improving ergonomics in physical human-robot interaction and reducing the risk of musculoskeletal disorders. Vision-based postur…