# CAREER: Enhancing Adaptability in Multimodal Human-Robot Interaction

> **NSF 01002526DB NSF RESEARCH & RELATED ACTIVIT** · University of Virginia Main Campus (VA) · $630,000

## Abstract

As robots become increasingly helpful in factories, hospitals, and homes, they must learn how to interact effectively with people. When people communicate, they use words and body language—like hand movements and eye contact—to share what they mean. In the same way, robots that work closely with people need to understand both verbal words and nonverbal signals. One major challenge in creating such robots is that people’s behavior can change over time. For example, a person may use different gestures (e.g., pointing vs eye gaze) to describe an object at different times. The robot must notice these changes and adjust its responses. Also, if the surroundings change, robots must change how they act to keep being helpful. This project will help robots understand people better by studying both verbal messages and nonverbal cues. It will also improve how robots learn and plan to adjust when people’s behavior changes. The results of this research will impact people and help them to be more accepting of robots. The project will help students in several ways. First, new topics will be added to robotics classes. Second, the research will involve high school and college students. Finally, the team will share robotic advancements with the public through outreach activities. 


This project will focus on three goals to address challenges in multimodal human-robot interactions. First, it will develop advanced algorithms to understand human intentions. These algorithms will use multimodal

## Key facts

- **NSF award ID:** 2441587
- **Awardee organization:** University of Virginia Main Campus (VA)
- **SAM.gov UEI:** JJG6HU8PA4S5
- **PI:** Tariq Iqbal
- **Primary program:** 01002526DB NSF RESEARCH & RELATED ACTIVIT
- **All programs:** CAREER-Faculty Erly Career Dev, Cyber-Human Systems
- **Estimated total:** $630,000
- **Funds obligated:** $377,674
- **Transaction type:** Continuing Grant
- **Period:** 06/15/2025 → 05/31/2030

## Primary source

NSF Award Search: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2441587

## Citation

> US National Science Foundation, Award 2441587, CAREER: Enhancing Adaptability in Multimodal Human-Robot Interaction. Retrieved via AI Analytics 2026-06-08 from https://api.ai-analytics.org/grant/nsf/2441587. Licensed CC0.

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