3 papers
cs.RO2025
LBAP: Improved Uncertainty Alignment of LLM Planners using Bayesian Inference
James F. Mullen, Dinesh Manocha
Large language models (LLMs) showcase many desirable traits for intelligent and helpful robots. However, they are also known to hallucinate predictions. This issue is exacerbated i…
cs.RO2025
HomeEmergency -- Using Audio to Find and Respond to Emergencies in the Home
James F. Mullen, Dhruva Kumar, Xuewei Qi +4
In the United States alone accidental home deaths exceed 128,000 per year. Our work aims to enable home robots who respond to emergency scenarios in the home, preventing injuries a…
cs.RO2024
"Don't forget to put the milk back!" Dataset for Enabling Embodied Agents to Detect Anomalous Situations
James F. Mullen, Prasoon Goyal, Robinson Piramuthu +3
Home robots intend to make their users lives easier. Our work assists in this goal by enabling robots to inform their users of dangerous or unsanitary anomalies in their home. Some…