REVIEW article
Front. Robot. AI
Sec. Human-Robot Interaction
Volume 12 - 2025 | doi: 10.3389/frobt.2025.1604472
Multimodal Perception-Driven Decision-Making for Human-Robot Interaction: A Survey
Provisionally accepted
- Worcester Polytechnic Institute, Worcester, United States
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Multimodal perception is essential for enabling robots to understand and interact with complex environments and human users by integrating diverse sensory data, such as vision, language, and tactile information. This capability plays a crucial role in decision-making in dynamic, complex environments. This survey provides a comprehensive review of advancements in multimodal perception and its integration with decision-making in robotics from year 2004 to 2024. We systematically summarize existing multimodal perception-driven decision-making (MPDDM) frameworks, highlighting their advantages in dynamic environments and the methodologies employed in human-robot interaction (HRI). Beyond reviewing these frameworks, we analyze key challenges in multimodal perception and decision-making, focusing on technical integration and sensor noise, adaptation, domain generalization, and safety and robustness. Finally, we outline future research directions, emphasizing the need for adaptive multimodal fusion techniques, more efficient learning paradigms, and human-trusted decision-making frameworks to advance the HRI field.
Keywords: Multimodal perception, Robot Decision-Making, human-robot interaction, multimodal fusion, robust autonomy
Received: 01 Apr 2025; Accepted: 05 Aug 2025.
Copyright: © 2025 Zhao, Gangaraju and Yuan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Fengpei Yuan, Worcester Polytechnic Institute, Worcester, United States
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