Research Topic 2: The Future of Robotic Teleoperation in Construction
Research Description
This research will immerse yourself in the exciting field of teleoperation in construction. You will have the opportunity to understand how operators remotely control machines to perform tasks in hazardous/extreme work contexts (e.g., demolition sites, space construction) and participate in the development of robotic teleoperation simulation. A digital twin model is developed to test novel human-machine interfaces ensuring that they help operators manipulate the machine robustly while reducing cognitive workload that can reduce performance and increase stress at work. Through experiments in a virtual environment, you will understand the challenges of human-robot interaction during teleoperation and contribute to the development of human-centered interfaces for robotic teleoperation in construction, enhancing critical thinking and problem-solving skills in construction robotics.
REU Research Plan
The REU student will be involved in designing a virtual model simulation and conducting teleoperation experiments, in collaboration with graduate student mentors and a faculty advisor. The student will first conduct a literature review to understand robotic teleoperation in construction (e.g., demolition sites, space construction). The student will be given tutoring and guidance on coding skills by graduate student mentors during the summer months, and also be given tasks to design and develop a digital twin model. The student will test the prototype simulation and analyze the outcomes using statistical methods. The student will be given an opportunity to write a conference/journal paper with the graduate student mentors and a faculty advisor.
More Details
Keywords: Robotic Teleoperation, Space Construction, Human-Robot Interaction, Virtual Reality
Required/Preferred Skills: Basic knowledge of statistics and coding (C# for unity)
Undergraduate Degrees: Computer Science, Civil Engineering, Building Construction, Construction Science/Management
Potential Faculty Advisor: Dr. Youngjib Ham