81 citations · 114 across the 14 of their papers we have counts for
14 papers
RoboTok: A Scalable Data Engine for Internet Demonstration Video Retrieval and Dexterous Manipulation Learning
Howard Qian, Yiting Chen, Yunfei Xie +6
Robot learning increasingly depends on broad and diverse demonstrations, yet collecting robot data remains expensive and difficult to scale across the wide range of real-world task…
EgoInfinity: A Web-Scale 4D Hand-Object Interaction Data Engine for Any-View Robot Retargeting and Video-to-Action Robot Learning
Gaotian Wang, Kejia Ren, Andrew Morgan +4
Internet videos constitute the largest reservoir of embodied human manipulation knowledge, yet converting arbitrary RGB footage into actionable robot training data remains a major…
ManipulationNet: An Infrastructure for Benchmarking Real-World Robot Manipulation with Physical Skill Challenges and Embodied Multimodal Reasoning
Yiting Chen, Kenneth Kimble, Edward H. Adelson +20
Dexterous manipulation enables robots to purposefully alter the physical world, transforming them from passive observers into active agents in unstructured environments. This capab…
rt-RISeg: Real-Time Model-Free Robot Interactive Segmentation for Active Instance-Level Object Understanding
Howard H. Qian, Yiting Chen, Gaotian Wang +2
Successful execution of dexterous robotic manipulation tasks in new environments, such as grasping, depends on the ability to proficiently segment unseen objects from the backgroun…
Robust Peg-in-Hole Assembly under Uncertainties via Compliant and Interactive Contact-Rich Manipulation
Yiting Chen, Kenneth Kimble, Howard H. Qian +3
Robust and adaptive robotic peg-in-hole assembly under tight tolerances is critical to various industrial applications. However, it remains an open challenge due to perceptual and…
B4P: Simultaneous Grasp and Motion Planning for Object Placement via Parallelized Bidirectional Forests and Path Repair
Benjamin H. Leebron, Kejia Ren, Yiting Chen +1
Robot pick and place systems have traditionally decoupled grasp, placement, and motion planning to build sequential optimization pipelines with the assumption that the individual c…
ARC-Calib: Autonomous Markerless Camera-to-Robot Calibration via Exploratory Robot Motions
Podshara Chanrungmaneekul, Yiting Chen, Joshua T. Grace +2
Camera-to-robot (also known as eye-to-hand) calibration is a critical component of vision-based robot manipulation. Traditional marker-based methods often require human interventio…
Implicit Articulated Robot Morphology Modeling with Configuration Space Neural Signed Distance Functions
Yiting Chen, Xiao Gao, Kunpeng Yao +3
In this paper, we introduce a novel approach to implicitly encode precise robot morphology using forward kinematics based on a configuration space signed distance function. Our pro…
Sliding Touch-based Exploration for Modeling Unknown Object Shape with Multi-fingered Hands
Yiting Chen, Ahmet Ercan Tekden, Marc Peter Deisenroth +1
Efficient and accurate 3D object shape reconstruction contributes significantly to the success of a robot's physical interaction with its environment. Acquiring accurate shape info…
Robot Cooking with Stir-fry: Bimanual Non-prehensile Manipulation of Semi-fluid Objects
Junjia Liu, Yiting Chen, Zhipeng Dong +4
This letter describes an approach to achieve well-known Chinese cooking art stir-fry on a bimanual robot system. Stir-fry requires a sequence of highly dynamic coordinated movement…
Learning Robotic Ultrasound Scanning Skills via Human Demonstrations and Guided Explorations
Xutian Deng, Yiting Chen, Fei Chen +1
Medical ultrasound has become a routine examination approach nowadays and is widely adopted for different medical applications, so it is desired to have a robotic ultrasound system…
Learning Friction Model for Tethered Capsule Robot
Yi Wang, Yuchen He, Xutian Deng +3
With the potential applications of capsule robots in medical endoscopy, accurate dynamic control of the capsule robot is becoming more and more important. In the scale of a capsule…
Data Generation for Learning to Grasp in a Bin-picking Scenario
Yiting Chen, Miao Li
The rise of deep learning has greatly transformed the pipeline of robotic grasping from model-based approach to data-driven stream. Along this line, a large scale of grasping data…
Unknown Object Segmentation through Domain Adaptation
Yiting Chen, Chenguang Yang, Miao Li
The ability to segment unknown objects in cluttered scenes has a profound impact on robot grasping. The rise of deep learning has greatly transformed the pipeline of robotic graspi…