2 citations · 5 across the 7 of their papers we have counts for
8 papers
Learning to Plan in Human-Robot Collaboration: Multimodal Reinforcement Learning for Adaptive Interaction
Afagh Mehri Shervedani, Siyu Li, Natawut Monaikul +3
Robot assistants for older adults and people with disabilities need to perform collaborative tasks with users effectively. The core component of these systems is an interaction man…
From Vague Instructions to Task Plans: A Feedback-Driven HRC Task Planning Framework based on LLMs
Afagh Mehri Shervedani, Matthew R. Walter, Milos Zefran
Recent advances in large language models (LLMs) have demonstrated their potential as planners in human-robot collaboration (HRC) scenarios, offering a promising alternative to trad…
Group-Control Motion Planning Framework for Microrobot Swarms in a Global Field
Siyu Li, Afagh Mehri Shervedani, Miloš Žefran +1
This paper investigates how a novel paradigm called group-control can be effectively used for motion planning for microrobot swarms in a global field. We prove that Small-Time Loca…
Proactive Robot Control for Collaborative Manipulation Using Human Intent
Zhanibek Rysbek, Siyu Li, Afagh Mehri Shervedani +1
Collaborative manipulation task often requires negotiation using explicit or implicit communication. An important example is determining where to move when the goal destination is…
An End-to-End Human Simulator for Task-Oriented Multimodal Human-Robot Collaboration
Afagh Mehri Shervedani, Siyu Li, Natawut Monaikul +3
This paper proposes a neural network-based user simulator that can provide a multimodal interactive environment for training Reinforcement Learning (RL) agents in collaborative tas…
Robots Taking Initiative in Collaborative Object Manipulation: Lessons from Physical Human-Human Interaction
Zhanibek Rysbek, Ki Hwan Oh, Afagh Mehri Shervedani +3
Physical Human-Human Interaction (pHHI) involves the use of multiple sensory modalities. Studies of communication through spoken utterances and gestures are well established, but c…