31 citations · 58 across the 38 of their papers we have counts for
45 papers
Evaluating Lightweight Contact Feedback in Dual-Operator Collaborative Humanoid Teleoperation
Austin Graves, Chuizheng Kong, Yunho Cho +4
Dual-operator humanoid teleoperation enables collaborative manipulation through two separate robots, but operators lack direct awareness of robot-object contact that is normally av…
Bilinear Flow Policy: Distributional Extrapolation for Goal-Conditioned Visuomotor Imitation
Wonsuhk Jung, Sundhar Vinodh Sangeetha, Chen Xu +4
Goal-conditioned imitation learning (GCIL) with flow matching is a promising framework that can represent multimodal behaviors while adapting to diverse, user-specified goals, yet…
Less Decoder is More Encoder: Geometric Representation Learning from Novel View Synthesis
Keerthi Kaashyap, Dennis Anthony, Akshay Krishnan +5
This paper examines the role of Novel View Synthesis (NVS) in geometric representation learning. In principle, NVS should reason about 3D scene structure, thereby enabling transfer…
MicroSplat: Towards Automating 3D Small-Scale Reconstruction
Roman Mineyev, Robert Azarcon, Suvrat Jain +2
Reconstructing sub-millimeter detail of small objects underpins tasks such as circuit-board defect detection, specimen digitization, and archiving. 3D Gaussian Splatting (3DGS) mak…
Expert-Play Contouring Control: Faster-than-Demonstration Planning from Slow Expert and Fast Play
Seunghoon Cho, Wonsuhk Jung, Sundhar Vinodh Sangeetha +1
Expert demonstrations often specify what a robot should do, but not how fast it can do it. Imitation Learning (IL) inherits demonstration timing, while directly accelerating the le…
Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation
Woo Chul Shin, Zhenyang Chen, Alfred Cueva +5
Visuomotor policies have advanced on manipulation tasks where the target object stays static during execution, but real deployments break this assumption: parts drift on conveyors…
ShardNet: Training Neural Controllers with Hard, Non-Convex Constraints
Long Kiu Chung, Shreyas Kousik
While neural network control policies are powerful, their deployment on safety critical systems depends on ensuring that they obey strict constraints. Existing work often treats sa…
Exact, Efficient, and Safe Occlusion-Aware Planning Using AH-Polyhedrons
Long Kiu Chung, David Isele, Toktam Mohammadnejad +4
Safely handling occlusions is a fundamental challenge for autonomous mobile robots operating in dynamic environments. This issue is especially prominent in autonomous valet parking…
WARP: Whole-Body Retargeting for Learning from Offline Human Demonstrations
Zhenyang Chen, Chuizheng Kong, Chuye Zhang +4
Direct transfer from human demonstration to learnable robot action is a crucial step towards scalable whole-body mobile manipulation. While human data scales better than mobile tel…
Make Your VLA More Robust Without More Data By Interleaving Motion Planning
Dan BW Choe, Sundhar Vinodh Sangeetha, Samuel Coogan +1
Vision-Language-Action (VLA) models have shown remarkable progress for mobile manipulation, but their performance on long-horizon tasks remains poor. These tasks are especially cha…
RTD-RAX: Fast, Safe Trajectory Planning for Systems under Unknown Disturbances
Evanns Morales-Cuadrado, Long Kiu Chung, Shreyas Kousik +1
Reachability-based Trajectory Design (RTD) is a provably safe, real-time trajectory planning framework that combines offline reachable-set computation with online trajectory optimi…
The Talking Robot: Distortion-Robust Acoustic Models for Robot-Robot Communication
Hanlong Li, Karishma Kamalahasan, Jiahui Li +2
We present Artoo, a learned acoustic communication system for robots that replaces hand-designed signal processing with end-to-end co-trained neural networks. Our system pairs a li…
Selecting Spots by Explicitly Predicting Intention from Motion History Improves Performance in Autonomous Parking
Long Kiu Chung, David Isele, Faizan M. Tariq +3
In many applications of social navigation, existing works have shown that predicting and reasoning about human intentions can help robotic agents make safer and more socially accep…
A Closed-Form Geometric Retargeting Solver for Upper Body Humanoid Robot Teleoperation
Chuizheng Kong, Yunho Cho, Wonsuhk Jung +11
Retargeting human motion to robot poses is a practical approach for teleoperating bimanual humanoid robot arms, but existing methods can be suboptimal and slow, often causing undes…
Going with the Flow: Koopman Behavioral Models as Pseudo Planners for Visuo-Motor Dexterity
Yunhai Han, Jiaqi Fu, Linhao Bai +7
Contemporary visuo-motor dexterity models often rely on expressive policy classes with diffusion and transformer backbones to achieve strong performance. However, these architectur…
Joint Model-based Model-free Diffusion for Planning with Constraints
Wonsuhk Jung, Utkarsh A. Mishra, Nadun Ranawaka Arachchige +3
Model-free diffusion planners have shown great promise for robot motion planning, but practical robotic systems often require combining them with model-based optimization modules t…
Ask, Reason, Assist: Robot Collaboration via Natural Language and Temporal Logic
Dan BW Choe, Sundhar Vinodh Sangeetha, Steven Emanuel +3
Increased robot deployment, such as in warehousing, has revealed a need for collaboration among heterogeneous robot teams to resolve unforeseen conflicts. To this end, we propose a…
Language Conditioning Improves Accuracy of Aircraft Goal Prediction in Non-Towered Airspace
Sundhar Vinodh Sangeetha, Chih-Yuan Chiu, Sarah H. Q. Li +1
Autonomous aircraft must safely operate in non-towered airspace, where coordination relies on voice-based communication among human pilots. Safe operation requires an aircraft to p…
SAIL: Faster-than-Demonstration Execution of Imitation Learning Policies
Nadun Ranawaka Arachchige, Zhenyang Chen, Wonsuhk Jung +8
Offline Imitation Learning (IL) methods such as Behavior Cloning are effective at acquiring complex robotic manipulation skills. However, existing IL-trained policies are confined…
Seeing, Saying, Solving: An LLM-to-TL Framework for Cooperative Robots
Dan BW Choe, Sundhar Vinodh Sangeetha, Steven Emanuel +3
Increased robot deployment, such as in warehousing, has revealed a need for seamless collaboration among heterogeneous robot teams to resolve unforeseen conflicts. To address this…
Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis
Long Kiu Chung, Shreyas Kousik
Even though neural networks are being increasingly deployed in safety-critical control applications, it remains difficult to enforce constraints on their output, meaning that it is…
RAIL: Reachability-Aided Imitation Learning for Safe Policy Execution
Wonsuhk Jung, Dennis Anthony, Utkarsh A. Mishra +4
Imitation learning (IL) has shown great success in learning complex robot manipulation tasks. However, there remains a need for practical safety methods to justify widespread deplo…
Towards Closing the Loop in Robotic Pollination for Indoor Farming via Autonomous Microscopic Inspection
Chuizheng Kong, Alex Qiu, Idris Wibowo +5
Effective pollination is a key challenge for indoor farming, since bees struggle to navigate without the sun. While a variety of robotic system solutions have been proposed, it rem…
Guaranteed Reach-Avoid for Black-Box Systems through Narrow Gaps via Neural Network Reachability
Long Kiu Chung, Wonsuhk Jung, Srivatsank Pullabhotla +6
In the classical reach-avoid problem, autonomous mobile robots are tasked to reach a goal while avoiding obstacles. However, it is difficult to provide guarantees on the robot's pe…