1 citations · 1 across the 16 of their papers we have counts for
17 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…
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…
V-VLAPS: Value-Guided Planning for Vision-Language-Action Models
Ke Ren, Ali Salamatian, Kieran Pattison +1
Vision-language-action (VLA) models provide strong action priors for robotic manipulation, but their reactive behavior can fail under distribution shift and long-horizon task struc…
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…
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…
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…
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…
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…
Deep Anticipation: Light Weight Intelligent Mobile Sensing in IoT by Recurrent Architecture
Guang Chen, Shu Liu, Kejia Ren +4
The rapid growth of IoT era is shaping the future of mobile services. Advanced communication technology enables a heterogeneous connectivity where mobile devices broadcast informat…