International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Multimodal AI-Enhanced Robotics for Real-Time Adaptive Collaboration in Dynamic Environments

Author(s) Mr. Dhananjay Yalawar, Ms. Anusha Yadav, Mrs. Sunanda Lingampally, Mrs. Swathi Jinnoji
Country India
Abstract The integration of multimodal artificial intelligence (AI) in robotics has emerged as a transformative paradigm, enabling robots to collaborate adaptively with humans and other autonomous systems in dynamic environments. By leveraging sensor fusion, deep learning, reinforcement learning, and context-aware decision-making, multimodal AI enhances perception, adaptability, and safety in real-time. This paper proposes a framework for multimodal AI-enhanced robotics, focusing on sensor fusion, AI-driven interpretation, and context-aware collaboration. The methodology outlines how robots utilize multimodal data inputs—including vision, speech, gesture, and environmental cues—to achieve adaptive behavior. Applications in manufacturing, healthcare, disaster response, and smart mobility are highlighted. Challenges such as data integration complexity, computational latency, and ethical considerations are also discussed. The findings underscore the transformative potential of multimodal AI in enabling real-time adaptive collaboration, paving the way for resilient, intelligent, and human-centric robotic ecosystems.
Keywords Multimodal AI, Robotics, Sensor Fusion, Adaptive Collaboration,
Field Computer > Automation / Robotics
Published In Volume 7, Issue 5, September-October 2025
Published On 2025-09-02
DOI https://doi.org/10.36948/ijfmr.2025.v07i05.54975
Short DOI https://doi.org/g92463
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