39 citations · 71 across the 14 of their papers we have counts for
14 papers
Propagating Unsafe Actions in LLM Controlled Multi-Robot Collaboration via Single Robot Compromise
Zhen Huang, Zhihuang Liu, Mengxuan Luo +2
Large language models (LLMs) are increasingly used as general planners in embodied intelligence, enabling high level coordination and low level task planning for both single robot…
Topology-Guided ORCA: Smooth Multi-Agent Motion Planning in Constrained Environments
Fatemeh Cheraghi Pouria, Zhe Huang, Ananya Yammanuru +2
We present Topology-Guided ORCA as an alternative simulator to replace ORCA for planning smooth multi-agent motions in environments with static obstacles. Despite the impressive pe…
LIT: Large Language Model Driven Intention Tracking for Proactive Human-Robot Collaboration -- A Robot Sous-Chef Application
Zhe Huang, John Pohovey, Ananya Yammanuru +1
Large Language Models (LLM) and Vision Language Models (VLM) enable robots to ground natural language prompts into control actions to achieve tasks in an open world. However, when…
Learning Task Skills and Goals Simultaneously from Physical Interaction
Haonan Chen, Ye-Ji Mun, Zhe Huang +4
In real-world human-robot systems, it is essential for a robot to comprehend human objectives and respond accordingly while performing an extended series of motor actions. Although…
Neural Informed RRT*: Learning-based Path Planning with Point Cloud State Representations under Admissible Ellipsoidal Constraints
Zhe Huang, Hongyu Chen, John Pohovey +1
Sampling-based planning algorithms like Rapidly-exploring Random Tree (RRT) are versatile in solving path planning problems. RRT* offers asymptotic optimality but requires growing…
Towards Safe Multi-Level Human-Robot Interaction in Industrial Tasks
Zhe Huang, Ye-Ji Mun, Haonan Chen +7
Multiple levels of safety measures are required by multiple interaction modes which collaborative robots need to perform industrial tasks with human co-workers. We develop three in…
User-Friendly Safety Monitoring System for Manufacturing Cobots
Ye-Ji Mun, Zhe Huang, Haonan Chen +4
Collaborative robots are being increasingly utilized in industrial production lines due to their efficiency and accuracy. However, the close proximity between humans and robots can…
Seamless Interaction Design with Coexistence and Cooperation Modes for Robust Human-Robot Collaboration
Zhe Huang, Ye-Ji Mun, Xiang Li +6
A robot needs multiple interaction modes to robustly collaborate with a human in complicated industrial tasks. We develop a Coexistence-and-Cooperation (CoCo) human-robot collabora…
Insights from an Industrial Collaborative Assembly Project: Lessons in Research and Collaboration
Tan Chen, Zhe Huang, James Motes +13
Significant progress in robotics reveals new opportunities to advance manufacturing. Next-generation industrial automation will require both integration of distinct robotic technol…
Hierarchical Intention Tracking for Robust Human-Robot Collaboration in Industrial Assembly Tasks
Zhe Huang, Ye-Ji Mun, Xiang Li +6
Collaborative robots require effective human intention estimation to safely and smoothly work with humans in less structured tasks such as industrial assembly, where human intentio…
Intention Aware Robot Crowd Navigation with Attention-Based Interaction Graph
Shuijing Liu, Peixin Chang, Zhe Huang +6
We study the problem of safe and intention-aware robot navigation in dense and interactive crowds. Most previous reinforcement learning (RL) based methods fail to consider differen…
Learning Sparse Interaction Graphs of Partially Detected Pedestrians for Trajectory Prediction
Zhe Huang, Ruohua Li, Kazuki Shin +1
Multi-pedestrian trajectory prediction is an indispensable element of autonomous systems that safely interact with crowds in unstructured environments. Many recent efforts in traje…
Long-term Pedestrian Trajectory Prediction using Mutable Intention Filter and Warp LSTM
Zhe Huang, Aamir Hasan, Kazuki Shin +2
Trajectory prediction is one of the key capabilities for robots to safely navigate and interact with pedestrians. Critical insights from human intention and behavioral patterns nee…
Online monitoring for safe pedestrian-vehicle interactions
Peter Du, Zhe Huang, Tianqi Liu +5
As autonomous systems begin to operate amongst humans, methods for safe interaction must be investigated. We consider an example of a small autonomous vehicle in a pedestrian zone…