4 citations · 8 across the 34 of their papers we have counts for
35 papers
PACER: Process-Aware VLA Policy Learning from Human Corrections for Robotic Disassembly
Chang Liu, Sibo Tian, Litian Gong +4
Robotic disassembly of end-of-life (EoL) products requires robots to accommodate product variation, follow prerequisite sequences, and approach components precisely for contact-ric…
NeurRAFT: Robot Motion Planning via Anchor-Level Flow Matching with Clearance-Aware Preference Tuning
Sibo Tian, Chang Liu, Minghui Zheng +1
Recent end-to-end neural motion planners generate trajectories from raw sensor observations, avoiding the privileged geometric models required by classical planners. However, colli…
Transforming Remanufacturing Automation with Large Language Models: A Forward-Looking Analysis with Case Studies
Chang Liu, Sara Behdad, Prabhakar Pagilla +2
With growing concerns about resource scarcity and environmental degradation, remanufacturing of end-of-life (EoL) products within the circular economy is attracting increasing atte…
Behavior Uncloning: Distilling Mode Redirection into Policy Weights without Inference-Time Steering
Hao Wang, Jiuzhou Lei, Dayou Li +5
Behavior-cloned policies often learn multiple behavior modes from demonstration datasets, including modes that are unsafe or otherwise undesired at deployment. For example, a polic…
Constrained MPC-Based Motion Planning for Morphing Quadrotors in Ultra-Narrow Passages under Limited Perception
Harsh Modi, Xiao Liang, Minghui Zheng
This paper introduces a motion planning framework to plan morphology and trajectory for morphing quadrotors under extremely constrained environments. We develop a novel obstacle av…
Flow Motion Policy: Manipulator Motion Planning with Flow Matching Models
Davood Soleymanzadeh, Xiao Liang, Minghui Zheng
Open-loop end-to-end neural motion planners have recently been proposed to improve motion planning for robotic manipulators. These methods enable planning directly from sensor obse…
Learning When to See and When to Feel: Adaptive Vision-Torque Fusion for Contact-Aware Manipulation
Jiuzhou Lei, Chang Liu, Yu She +2
Vision-based policies have achieved a good performance in robotic manipulation due to the accessibility and richness of visual observations. However, purely visual sensing becomes…
Toward Generalist Neural Motion Planners for Robotic Manipulators: Challenges and Opportunities
Davood Soleymanzadeh, Ivan Lopez-Sanchez, Hao Su +3
State-of-the-art generalist manipulation policies have enabled the deployment of robotic manipulators in unstructured human environments. However, these frameworks struggle in clut…
Egocentric World Model for Photorealistic Hand-Object Interaction Synthesis
Dayou Li, Lulin Liu, Bangya Liu +6
To serve as a scalable data source for embodied AI, world models should act as true simulators that infer interaction dynamics strictly from user actions, rather than mere conditio…
Learning Actionable Manipulation Recovery via Counterfactual Failure Synthesis
Dayou Li, Jiuzhou Lei, Hao Wang +6
While recent foundation models have significantly advanced robotic manipulation, these systems still struggle to autonomously recover from execution errors. Current failure-learnin…
SELF-VLA: A Skill Enhanced Agentic Vision-Language-Action Framework for Contact-Rich Disassembly
Chang Liu, Sibo Tian, Xiao Liang +1
Disassembly automation has long been pursued to address the growing demand for efficient and proper recovery of valuable components from the end-of-life (EoL) electronic products.…
TATIC: Task-Aware Temporal Learning for Human Intent Inference from Physical Corrections in Human-Robot Collaboration
Jiurun Song, Xiao Liang, Minghui Zheng
In human-robot collaboration (HRC), robots must adapt online to dynamic task constraints and evolving human intent. While physical corrections provide a natural, low-latency channe…
DRAFTO: Decoupled Reduced-space and Adaptive Feasibility-repair Trajectory Optimization for Robotic Manipulators
Yichang Feng, Xiao Liang, Minghui Zheng
This paper introduces a new algorithm for trajectory optimization, Decoupled Reduced-space and Adaptive Feasibility-repair Trajectory Optimization (DRAFTO). It first constructs a c…
GAIDE: Graph-based Attention Masking for Spatial- and Embodiment-aware Motion Planning
Davood Soleymanzadeh, Xiao Liang, Minghui Zheng
Sampling-based motion planning algorithms are widely used for motion planning of robotic manipulators, but they often struggle with sample inefficiency in high-dimensional configur…
CONTACT: CONtact-aware TACTile Learning for Robotic Disassembly
Yosuke Saka, Jyun-Chi Hu, Adeesh Desai +6
Robotic disassembly involves contact-rich interactions in which successful manipulation depends not only on geometric alignment but also on force-dependent state transitions. While…
Modular Safety Guardrails Are Necessary for Foundation-Model-Enabled Robots in the Real World
Joonkyung Kim, Wenxi Chen, Davood Soleymanzadeh +9
The integration of foundation models (FMs) into robotics has accelerated real-world deployment, while introducing new safety challenges arising from open-ended semantic reasoning a…
PrediFlow: A Flow-Based Prediction-Refinement Framework for Real-Time Human Motion Prediction in Human-Robot Collaboration
Sibo Tian, Minghui Zheng, Xiao Liang
Stochastic human motion prediction is critical for safe and effective human-robot collaboration (HRC) in industrial remanufacturing, as it captures human motion uncertainties and m…
Vision-Language-Action Models for Selective Robotic Disassembly: A Case Study on Critical Component Extraction from Desktops
Chang Liu, Sibo Tian, Sara Behdad +2
Automating disassembly of critical components from end-of-life (EoL) desktops, such as high-value items like RAM modules and CPUs, as well as sensitive parts like hard disk drives,…
PerFACT: Motion Policy with LLM-Powered Dataset Synthesis and Fusion Action-Chunking Transformers
Davood Soleymanzadeh, Xiao Liang, Minghui Zheng
Deep learning methods have significantly enhanced motion planning for robotic manipulators by leveraging prior experiences within planning datasets. However, state-of-the-art neura…
ANGEL: A Novel Gripper for Versatile and Light-touch Fruit Harvesting
Dharmik Patel, Antonio Rafael Vazquez Pantoja, Jiuzhou Lei +3
Fruit harvesting remains predominantly a labor-intensive process, motivating the development of research for robotic grippers. Conventional rigid or vacuum-driven grippers require…
DeGrip: A Compact Cable-driven Robotic Gripper for Desktop Disassembly
Bihao Zhang, Davood Soleymanzadeh, Xiao Liang +1
Intelligent robotic disassembly of end-of-life (EOL) products has been a long-standing challenge in robotics. While machine learning techniques have shown promise, the lack of spec…
Adaptive Motion Planning via Contact-Based Intent Inference for Human-Robot Collaboration
Jiurun Song, Xiao Liang, Minghui Zheng
Human-robot collaboration (HRC) requires robots to adapt their motions to human intent to ensure safe and efficient cooperation in shared spaces. Although large language models (LL…
Warm-Starting Optimization-Based Motion Planning for Robotic Manipulators via Point Cloud-Conditioned Flow Matching
Sibo Tian, Minghui Zheng, Xiao Liang
Rapid robot motion generation is critical in Human-Robot Collaboration (HRC) systems, as robots need to respond to dynamic environments in real time by continuously observing their…
RAISE: A Robot-Assisted Selective Disassembly and Sorting System for End-of-Life Phones
Chang Liu, Badrinath Balasubramaniam, Neal Yancey +6
End-of-Life (EoL) phones significantly exacerbate global e-waste challenges due to their high production volumes and short lifecycles. Disassembly is among the most critical proces…