Alex Ramirez — accepted AI-conference papers

2026

LLM-Driven Expressive Robot Motion Via Proxy-Based Optimization

Liam Roy, Elizabeth A. Croft, Alex Ramirez, Dana Kulic

RA-L 2026

Nonverbal communication through expressive robot motion significantly enhances human-robot interaction (HRI), yet designing motions that are both individually legible and collectively distinguishable remains challenging. Existing large language model (LLM)-based methods can successfully generate exp

Cited by 0 Source ↗code ↗Scholar ↗

2025

GPT-Driven Gestures: Leveraging Large Language Models to Generate Expressive Robot Motion for Enhanced Human-Robot Interaction

Liam Roy, Elizabeth A. Croft, Alex Ramirez, Dana Kulic

RA-L 2025

Expressive robot motion is a form of nonverbal communication that enables robots to convey their internal states, fostering effective human-robot interaction. A key step in designing expressive robot motions is developing a mapping from the desired states the robot will express to the robot's hardwa

Cited by 10 Source ↗Scholar ↗