36 citations · 40 across the 15 of their papers we have counts for
8 papers · 1 filter
Creating and Repairing Robot Programs in Open-World Domains
Claire Schlesinger, Arjun Guha, Joydeep Biswas
Using Large Language Models (LLMs) to produce robot programs from natural language has allowed for robot systems that can complete a higher diversity of tasks. However, LLM-generat…
Joint Verification and Refinement of Language Models for Safety-Constrained Planning
Yunhao Yang, Neel P. Bhatt, William Ward +3
Large language models possess impressive capabilities in generating programs (e.g., Python) from natural language descriptions to execute robotic tasks. However, these generated pr…
Lessons Learned from Developing a Human-Centered Guide Dog Robot for Mobility Assistance
Hochul Hwang, Ken Suzuki, Nicholas A Giudice +3
While guide dogs offer essential mobility assistance, their high cost, limited availability, and care requirements make them inaccessible to most blind or low vision (BLV) individu…
Robo-Instruct: Simulator-Augmented Instruction Alignment For Finetuning Code LLMs
Zichao Hu, Junyi Jessy Li, Arjun Guha +1
Code LLMs have shown promising results with converting tasks in natural language to programs that can be executed by service robots. We are interested in finetuning small, speciali…
Dynamic Model Predictive Shielding for Provably Safe Reinforcement Learning
Arko Banerjee, Kia Rahmani, Joydeep Biswas +1
Among approaches for provably safe reinforcement learning, Model Predictive Shielding (MPS) has proven effective at complex tasks in continuous, high-dimensional state spaces, by l…
Vid2Real HRI: Align video-based HRI study designs with real-world settings
Elliott Hauser, Yao-Cheng Chan, Sadanand Modak +2
HRI research using autonomous robots in real-world settings can produce results with the highest ecological validity of any study modality, but many difficulties limit such studies…
SYNAPSE: SYmbolic Neural-Aided Preference Synthesis Engine
Sadanand Modak, Noah Patton, Isil Dillig +1
This paper addresses the problem of preference learning, which aims to align robot behaviors through learning user specific preferences (e.g. "good pull-over location") from visual…
Towards Robotic Companions: Understanding Handler-Guide Dog Interactions for Informed Guide Dog Robot Design
Hochul Hwang, Hee-Tae Jung, Nicholas A Giudice +3
Dog guides are favored by blind and low-vision (BLV) individuals for their ability to enhance independence and confidence by reducing safety concerns and increasing navigation effi…