Robotic Dough Shaping
원문 초록
Robotic manipulation of deformable objects gains great attention due to its wide applications including medical surgery, home assistance, and automatic food preparation. The ability to deform soft objects remains a great challenge for robots due to difficulties in defining the problem mathematically. In this paper, we address the problem of shaping a piece of dough-like deformable material into a 2D target shape presented upfront. We use a 6 degree-of-freedom WidowX-250 Robot Arm equipped with a rolling pin and information collected from an RGB-D camera and a tactile sensor. We present and compare several control policies, including a dough shrinking action, in extensive experiments across three kinds of deformable materials and across three target dough shape sizes, achieving the intersection over union (IoU) of 0.90. Our results show that: i) rolling dough from the highest dough point is more efficient than from the 2D/3D dough centroid; ii) it might be better to stop the roll movement at the current dough boundary as opposed to the target shape outline; iii) the shrink action might be beneficial only if properly tuned with respect to the expand action; and iv) the Play-Doh material is easier to shape to a target shape as compared to Plasticine or Kinetic sand. Video demonstrations of our work are available at https://youtu.be/ZzLMxuITdt4
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Reduced-Order Neural Operators: Learning Lagrangian Dynamics on Highly Sparse Graphs
AoSRNet: All-in-One Scene Recovery Networks via Multi-knowledge Integration
Watermarks in the Sand: Impossibility of Strong Watermarking for Generative Models
Pretrained Language Models as Visual Planners for Human Assistance
RMMDet: Road-Side Multitype and Multigroup Sensor Detection System for Autonomous Driving
Learning to Simulate Daily Activities via Modeling Dynamic Human Needs
토론
이 논문과 연결된 포럼 글이 아직 없습니다.