Keywords
augmented reality
speech recognition
How to Cite
Abstract
Human-robot interaction (HRI) plays a crucial role in enabling seamless collaboration between humans and robots in various domains, including healthcare, manufacturing, and service industries. Effective HRI relies on intuitive interfaces and modalities that allow humans to communicate with and control robots efficiently. This paper explores the current state of interfaces and modalities for HRI, focusing on their design principles, implementation challenges, and applications. We discuss key technologies such as speech recognition, gesture recognition, haptic feedback, and augmented reality, highlighting their strengths and limitations. Additionally, we examine the impact of cultural and social factors on HRI design and propose future research directions to enhance HRI experiences.
References
Tatineni, Sumanth. "Climate Change Modeling and Analysis: Leveraging Big Data for Environmental Sustainability." International Journal of Computer Engineering and Technology 11.1 (2020).
Gudala, Leeladhar, Mahammad Shaik, and Srinivasan Venkataramanan. "Leveraging Machine Learning for Enhanced Threat Detection and Response in Zero Trust Security Frameworks: An Exploration of Real-Time Anomaly Identification and Adaptive Mitigation Strategies." Journal of Artificial Intelligence Research 1.2 (2021): 19-45.
Tatineni, Sumanth. "Enhancing Fraud Detection in Financial Transactions using Machine Learning and Blockchain." International Journal of Information Technology and Management Information Systems (IJITMIS) 11.1 (2020): 8-15.