5 citations · 10 across the 9 of their papers we have counts for
9 papers
Pre-Execution Safety Gate & Task Safety Contracts for LLM-Controlled Robot Systems
Ike Obi, Vishnunandan L. N. Venkatesh, Weizheng Wang +5
Large Language Models (LLMs) are increasingly used to convert task commands into robot-executable code, however this pipeline lacks validation gates to detect unsafe and defective…
Multi-Agent LLM Actor-Critic Framework for Social Robot Navigation
Weizheng Wang, Ike Obi, Byung-Cheol Min
Recent advances in robotics and large language models (LLMs) have sparked growing interest in human-robot collaboration and embodied intelligence. To enable the broader deployment…
SafePlan: Leveraging Formal Logic and Chain-of-Thought Reasoning for Enhanced Safety in LLM-based Robotic Task Planning
Ike Obi, Vishnunandan L. N. Venkatesh, Weizheng Wang +5
Robotics researchers increasingly leverage large language models (LLM) in robotics systems, using them as interfaces to receive task commands, generate task plans, form team coalit…
Value Imprint: A Technique for Auditing the Human Values Embedded in RLHF Datasets
Ike Obi, Rohan Pant, Srishti Shekhar Agrawal +2
LLMs are increasingly fine-tuned using RLHF datasets to align them with human preferences and values. However, very limited research has investigated which specific human values ar…
Identifying Factors Contributing to Bad Days for Software Developers: A Mixed Methods Study
Ike Obi, Jenna Butler, Sankeerti Haniyur +3
Software development is a dynamic activity that requires engineers to work effectively with tools, processes, and collaborative teams. As a result, the presence of friction can sig…
Modeling and Evaluating Trust Dynamics in Multi-Human Multi-Robot Task Allocation
Ike Obi, Ruiqi Wang, Wonse Jo +1
Trust is essential in human-robot collaboration, particularly in multi-human, multi-robot (MH-MR) teams, where it plays a crucial role in maintaining team cohesion in complex opera…
Adaptive Task Allocation in Multi-Human Multi-Robot Teams under Team Heterogeneity and Dynamic Information Uncertainty
Ziqin Yuan, Ruiqi Wang, Taehyeon Kim +3
Task allocation in multi-human multi-robot (MH-MR) teams presents significant challenges due to the inherent heterogeneity of team members, the dynamics of task execution, and the…
PrefCLM: Enhancing Preference-based Reinforcement Learning with Crowdsourced Large Language Models
Ruiqi Wang, Dezhong Zhao, Ziqin Yuan +2
Preference-based reinforcement learning (PbRL) is emerging as a promising approach to teaching robots through human comparative feedback, sidestepping the need for complex reward e…
Unifying Large Language Model and Deep Reinforcement Learning for Human-in-Loop Interactive Socially-aware Navigation
Weizheng Wang, Ike Obi, Aniket Bera +1
Navigating human-filled spaces is crucial for the interactive social robots to support advanced services, such as cooperative carrying, which enables service provision in complex a…