Multimodal Human-Robot Collaboration: A literature review

Abstract

Integrating robots into everyday human environments demands efficient and natural collaboration methods. Multimodal collaboration uses multiple methods of communication at the same time to improve human-robot interaction. This thesis is a literary review about the foundations, techniques, applications, and challenges of multimodal human-robot collaboration (HRC). The goal of the study is to combine information from various sources about the past, current and future state of multimodal HRC.

This thesis is split into parts that focus on the foundations, techniques, applications, and future directions of HRC. The study explores historical developments from early multimodal interfaces to current applications in industrial and social settings. Over time it has been found that combining multiple modalities such as speech, gestures, vision, haptics, and physiological sensing improves task allocation, communication, and adaptability in dynamic environments. Furthermore, a split into both explicit and implicit coordination techniques is presented. Challenges such as technological limitations, ethical concerns, privacy issues, and cognitive load are analysed, along with future directions like proactive collaboration, large language models, embodied intelligence, and real-time emotional interpretation.

Through this literature review, it becomes clear that while multimodal systems have advanced significantly, further research on the different modalities is needed to achieve seamless, trustworthy, and context-sensitive human-robot teamwork. Despite considerable advances, multimodal systems are not yet a ubiquitous or indispensable part of computing. Research must continue both in enhancing individual modalities, such as speech recognition, vision-based tracking, and haptics, and in developing cohesive methods for integrating them effectively. Addressing challenges like cognitive load, system robustness under diverse conditions, and privacy concerns will be critical for widespread adoption. The development of comprehensive design frameworks and best practices remains essential to ensure that multimodal interfaces become natural, reliable, and trustworthy tools for human-robot collaboration.