Date of Award


Document Type


Degree Name

Master of Science (MS)


College of Science and Mathematics


Computer Science

Thesis Sponsor/Dissertation Chair/Project Chair

Aparna Varde

Committee Member

Weitian Wang

Committee Member

Vaibhav Anu


Human-robot collaboration (HRC), where humans and robots work together on specific tasks, is a growing part of smart manufacturing that entails artificial intelligence (AI) techniques in manufacturing processes. Robots need to be able to dynamically understand their working environments and human partners both accurately and quickly, as inaccurate or slow predictions can be dangerous to humans and collaborative tasks. To handle challenging environments, robots need to utilize commonsense knowledge (CSK), which is everyday knowledge about fundamental concepts, such as how basic objects interact with each other, what their properties are, and how they are associated. Human beings utilize CSK regularly, and robots can effectively collaborate with humans through it. This thesis outlines the fundamentals of CSK to provide prerequisite information and demonstrates how robots utilize it to collaborate with humans. The thesis also demonstrates the effectiveness of CSK and HRC through simulation studies and real-world human-robot collaboration experiments by deploying commonsense knowledge priorities and mathematical modeling for task optimization in robot action planning. Human-robot collaboration is compared with humans working without aid from robots. This thesis presents the results of this work along with a survey of relevant literature, as well as open issues for further research. To the best of our knowledge, ours is pioneering work on proposing a specific approach based on commonsense knowledge for human-robot collaboration in smart manufacturing.

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