[2603.23271] A Multimodal Framework for Human-Multi-Agent Interaction

[2603.23271] A Multimodal Framework for Human-Multi-Agent Interaction

arXiv - AI 3 min read

About this article

Abstract page for arXiv paper 2603.23271: A Multimodal Framework for Human-Multi-Agent Interaction

Computer Science > Robotics arXiv:2603.23271 (cs) [Submitted on 24 Mar 2026] Title:A Multimodal Framework for Human-Multi-Agent Interaction Authors:Shaid Hasan, Breenice Lee, Sujan Sarker, Tariq Iqbal View a PDF of the paper titled A Multimodal Framework for Human-Multi-Agent Interaction, by Shaid Hasan and 3 other authors View PDF HTML (experimental) Abstract:Human-robot interaction is increasingly moving toward multi-robot, socially grounded environments. Existing systems struggle to integrate multimodal perception, embodied expression, and coordinated decision-making in a unified framework. This limits natural and scalable interaction in shared physical spaces. We address this gap by introducing a multimodal framework for human-multi-agent interaction in which each robot operates as an autonomous cognitive agent with integrated multimodal perception and Large Language Model (LLM)-driven planning grounded in embodiment. At the team level, a centralized coordination mechanism regulates turn-taking and agent participation to prevent overlapping speech and conflicting actions. Implemented on two humanoid robots, our framework enables coherent multi-agent interaction through interaction policies that combine speech, gesture, gaze, and locomotion. Representative interaction runs demonstrate coordinated multimodal reasoning across agents and grounded embodied responses. Future work will focus on larger-scale user studies and deeper exploration of socially grounded multi-agent ...

Originally published on March 25, 2026. Curated by AI News.

Related Articles

Robotics

AI system learns to prevent warehouse robot traffic jams, boosting throughput 25%

"Inside a giant autonomous warehouse, hundreds of robots dart down aisles as they collect and distribute items to fulfill a steady stream...

Reddit - Artificial Intelligence · 1 min ·
[2603.16673] When Should a Robot Think? Resource-Aware Reasoning via Reinforcement Learning for Embodied Robotic Decision-Making
Llms

[2603.16673] When Should a Robot Think? Resource-Aware Reasoning via Reinforcement Learning for Embodied Robotic Decision-Making

Abstract page for arXiv paper 2603.16673: When Should a Robot Think? Resource-Aware Reasoning via Reinforcement Learning for Embodied Rob...

arXiv - Machine Learning · 4 min ·
[2512.22854] ByteLoom: Weaving Geometry-Consistent Human-Object Interactions through Progressive Curriculum Learning
Machine Learning

[2512.22854] ByteLoom: Weaving Geometry-Consistent Human-Object Interactions through Progressive Curriculum Learning

Abstract page for arXiv paper 2512.22854: ByteLoom: Weaving Geometry-Consistent Human-Object Interactions through Progressive Curriculum ...

arXiv - Machine Learning · 4 min ·
[2511.14427] Self-Supervised Multisensory Pretraining for Contact-Rich Robot Reinforcement Learning
Machine Learning

[2511.14427] Self-Supervised Multisensory Pretraining for Contact-Rich Robot Reinforcement Learning

Abstract page for arXiv paper 2511.14427: Self-Supervised Multisensory Pretraining for Contact-Rich Robot Reinforcement Learning

arXiv - Machine Learning · 4 min ·
More in Robotics: This Week Guide Trending

No comments

No comments yet. Be the first to comment!

Stay updated with AI News

Get the latest news, tools, and insights delivered to your inbox.

Daily or weekly digest • Unsubscribe anytime