49 citations · 125 across the 28 of their papers we have counts for
32 papers
What Matters in Quality-Aware VLA Pretraining: A Benchmark and Empirical Study
Mingxuan Yan, Litian Gong, Dihong Huang +19
How should demonstration quality be used during vision-language-action (VLA) pretraining to improve performance after target-task fine-tuning? We compare weighting, filtering, and…
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…
Zero-Shot Sim-to-Real Robot Learning: A Dexterous Manipulation Study on Reactive Catching
Kejia Ren, Gaotian Wang, Andrew S. Morgan +1
Dexterous manipulation is physics-intensive and highly sensitive to modeling errors and perception noise, making sim-to-real transfer prohibitively challenging. Domain randomizatio…
ManiDreams: An Open-Source Library for Robust Object Manipulation via Uncertainty-aware Task-specific Intuitive Physics
Gaotian Wang, Kejia Ren, Andrew S. Morgan +1
Dynamics models, whether simulators or learned world models, have long been central to robotic manipulation, but most focus on minimizing prediction error rather than confronting a…
MotionBits: Video Segmentation through Motion-Level Analysis of Rigid Bodies
Howard H. Qian, Kejia Ren, Yu Xiang +2
Rigid bodies constitute the smallest manipulable elements in the real world, and understanding how they physically interact is fundamental to embodied reasoning and robotic manipul…
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…
Collision-Inclusive Manipulation Planning for Occluded Object Grasping via Compliant Robot Motions
Kejia Ren, Gaotian Wang, Andrew S. Morgan +1
Robotic manipulation research has investigated contact-rich problems and strategies that require robots to intentionally collide with their environment, to accomplish tasks that ca…
Efficient Multi-Robot Motion Planning for Manifold-Constrained Manipulators by Randomized Scheduling and Informed Path Generation
Weihang Guo, Zachary Kingston, Kaiyu Hang +1
Multi-robot motion planning for high degree-of-freedom manipulators in shared, constrained, and narrow spaces is a complex problem and essential for many scenarios such as construc…
Caging in Time: A Framework for Robust Object Manipulation under Uncertainties and Limited Robot Perception
Gaotian Wang, Kejia Ren, Andrew S. Morgan +1
Real-world object manipulation has been commonly challenged by physical uncertainties and perception limitations. Being an effective strategy, while caging configuration-based mani…
Object-Centric Kinodynamic Planning for Nonprehensile Robot Rearrangement Manipulation
Kejia Ren, Gaotian Wang, Andrew S. Morgan +2
Nonprehensile actions such as pushing are crucial for addressing multi-object rearrangement problems. Many traditional methods generate robot-centric actions, which differ from int…
UNO Push: Unified Nonprehensile Object Pushing via Non-Parametric Estimation and Model Predictive Control
Gaotian Wang, Kejia Ren, Kaiyu Hang
Nonprehensile manipulation through precise pushing is an essential skill that has been commonly challenged by perception and physical uncertainties, such as those associated with c…
Interactive Robot-Environment Self-Calibration via Compliant Exploratory Actions
Podshara Chanrungmaneekul, Kejia Ren, Joshua T. Grace +2
Calibrating robots into their workspaces is crucial for manipulation tasks. Existing calibration techniques often rely on sensors external to the robot (cameras, laser scanners, et…
RISeg: Robot Interactive Object Segmentation via Body Frame-Invariant Features
Howard H. Qian, Yangxiao Lu, Kejia Ren +4
In order to successfully perform manipulation tasks in new environments, such as grasping, robots must be proficient in segmenting unseen objects from the background and/or other o…
Wearable Roller Rings to Augment In-Hand Manipulation through Active Surfaces
Hayden Webb, Podshara Chanrungmaneekul, Shenli Yuan +1
In-hand manipulation is a crucial ability for reorienting and repositioning objects within grasps. The main challenges in this are not only the complexity of the computational mode…
Non-Parametric Self-Identification and Model Predictive Control of Dexterous In-Hand Manipulation
Podshara Chanrungmaneekul, Kejia Ren, Joshua T. Grace +2
Building hand-object models for dexterous in-hand manipulation remains a crucial and open problem. Major challenges include the difficulty of obtaining the geometric and dynamical…
Kinodynamic Rapidly-exploring Random Forest for Rearrangement-Based Nonprehensile Manipulation
Kejia Ren, Podshara Chanrungmaneekul, Lydia E. Kavraki +1
Rearrangement-based nonprehensile manipulation still remains as a challenging problem due to the high-dimensional problem space and the complex physical uncertainties it entails. W…
Self-Supervised Unseen Object Instance Segmentation via Long-Term Robot Interaction
Yangxiao Lu, Ninad Khargonkar, Zesheng Xu +6
We introduce a novel robotic system for improving unseen object instance segmentation in the real world by leveraging long-term robot interaction with objects. Previous approaches…
Rearrangement-Based Manipulation via Kinodynamic Planning and Dynamic Planning Horizons
Kejia Ren, Lydia E. Kavraki, Kaiyu Hang
Robot manipulation in cluttered environments often requires complex and sequential rearrangement of multiple objects in order to achieve the desired reconfiguration of the target o…
Complex In-Hand Manipulation via Compliance-Enabled Finger Gaiting and Multi-Modal Planning
Andrew S. Morgan, Kaiyu Hang, Bowen Wen +2
Constraining contacts to remain fixed on an object during manipulation limits the potential workspace size, as motion is subject to the hand's kinematic topology. Finger gaiting is…