Collection

Cognitive Computing for Human-Robot Interaction

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Closed

The design and development of Human-Robot Interaction (HRI) based applications are continuously increasing over the years. This increase in the event of HRI based real-world applications plays a significant role in the areas of automation in healthcare, education, entertainment, and many others. Since, HRI is widely innovative and is an integration of multiple disciplines like intelligence, computer science, natural language processing, psychology, robotics, etc. it has to withstand many hazardous environments and extreme situations. Moreover, there may be many cross-domain challenges, either intelligence or autonomy, in deploying this robotic system. In certain conditions, the HRI system used will also have interaction related problems which are uncertain, complex, and unpredictable. To manage this change of increasing challenges in HRI, the implementation of cognitive computing and techniques will improve the focus of interaction by providing accurate recommendations and solutions with reduced complexities.

Cognitive computing can imitate human intelligence and process information that can revolutionize the current existing system. It provides various advantages when combined with the HRI, such as accurate analysis for complex data, analyzes critical information in real-time, enhances human-robot interaction, cross-domain integrations, and many others. Due to its unique self-learning mechanism with the help of machine learning models, it is capable of facilitating expert assistance with deep insights without human intervention. In healthcare, manufacturing, and service sectors, cognitive computing can perform more effectively with HRI, thereby analyzing and assisting based on the need of the environment.

With the scope of the cognitive solution having a wide range of impact in HRI, there also arises certain limitations like information analyzing risks due to unstructured data, sophisticated training of data, and critical decision making based on the real-time scenario. However, effective planning with advanced technologies and adopting cognitive solutions can provide a complete solution for HRI and its applications. Since HRI has emerged as an essential research area in the recent years, this special issue titled "Cognitive Computing For Human-Robot Interaction" invites researchers and professionals from various industries to contribute their research papers including technical, behavioral, theoretical and methodological aspects of cognitive computing in Human-Robot Interaction (HRI).

Editors

  • Gunasekaran Manogaran Gunasekaran Manogaran , 

    Gunasekaran Manogaran

    Dr. Gunasekaran Manogaran is currently working as a Big Data Scientist in University of California, Davis, USA. He is also an Adjunct Assistant Professor, Department of Computer Science & Information Engineering, Asia University, Taiwan and Adjunct Faculty, in School of Computing, SRM Institute of Science and Technology, Kattankulathur, India. He is a visiting researcher/scientist in University of La Frontera, Colombia and International University of La Rioja, Spain.

  • Hassan Qudrat-Ullah Hassan Qudrat-Ullah  &

    Hassan Qudrat-Ullah

    Dr. Hassan Qudrat-Ullah earned his Ph. D. (Decision Sciences) in 2002 from NUS Business School, National University of Singapore. Hassan did post-doctoral fellowship at Carnegie Mellon University, USA, in 2002-2003 before joining York University in 2003. His research contributions from 2011 to 2014 include two books Better Decision Making in Complex, Dynamics Tasks (Springer, 2014), and an edited volume Energy Policy Modeling in 21st Century (Springer, 2013); he also contributed seven journal articles, two book chapters and he has also been invited to several conference proceedings and invited talks.

  • Qin Xin Qin Xin

    Qin Xin

    Dr. Qin Xin graduated with his Ph.D. in Department of Computer Science at University of Liverpool, UK in December 2004. Currently, he is working as a professor of Computer Science in the Faculty of Science and Technology at the University of the Faroe Islands (UoFI), Faroe Islands. Prior to joining UoFI, he had held variant research positions in world leading universities and research laboratory including Senior Research Fellowship at Universite Catholique de Louvain, Belgium, Research Scientist/Postdoctoral Research Fellowship at Simula Research Laboratory, Norway and Postdoctoral Research Fellowship at University of Bergen, Norway.

Articles (2 in this collection)