14 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…
Redefining End-of-Life: Intelligent Automation for Electronics Remanufacturing Systems
Sibo Tian, Xiao Liang, Sara Behdad +1
Remanufacturing is fundamentally more challenging than traditional manufacturing due to the significant uncertainty, variability, and incompleteness inherent in end-of-life (EoL) p…
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.…
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,…
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…
Bayesian-Optimized One-Step Diffusion Model with Knowledge Distillation for Real-Time 3D Human Motion Prediction
Sibo Tian, Minghui Zheng, Xiao Liang
Human motion prediction is a cornerstone of human-robot collaboration (HRC), as robots need to infer the future movements of human workers based on past motion cues to proactively…
Grasping Force Control and Adaptation for a Cable-Driven Robotic Hand
Eric Mountain, Ean Weise, Sibo Tian +3
This paper introduces a unique force control and adaptation algorithm for a lightweight and low-complexity five-fingered robotic hand, namely an Integrated-Finger Robotic Hand (IFR…
Integrating Uncertainty-Aware Human Motion Prediction into Graph-Based Manipulator Motion Planning
Wansong Liu, Kareem Eltouny, Sibo Tian +2
There has been a growing utilization of industrial robots as complementary collaborators for human workers in re-manufacturing sites. Such a human-robot collaboration (HRC) aims to…
KG-Planner: Knowledge-Informed Graph Neural Planning for Collaborative Manipulators
Wansong Liu, Kareem Eltouny, Sibo Tian +2
This paper presents a novel knowledge-informed graph neural planner (KG-Planner) to address the challenge of efficiently planning collision-free motions for robots in high-dimensio…
A Recurrent Neural Network Enhanced Unscented Kalman Filter for Human Motion Prediction
Wansong Liu, Sibo Tian, Boyi Hu +2
This paper presents a deep learning enhanced adaptive unscented Kalman filter (UKF) for predicting human arm motion in the context of manufacturing. Unlike previous network-based m…
TransFusion: A Practical and Effective Transformer-based Diffusion Model for 3D Human Motion Prediction
Sibo Tian, Minghui Zheng, Xiao Liang
Predicting human motion plays a crucial role in ensuring a safe and effective human-robot close collaboration in intelligent remanufacturing systems of the future. Existing works c…
DE-TGN: Uncertainty-Aware Human Motion Forecasting using Deep Ensembles
Kareem A. Eltouny, Wansong Liu, Sibo Tian +2
Ensuring the safety of human workers in a collaborative environment with robots is of utmost importance. Although accurate pose prediction models can help prevent collisions betwee…