The aim of the proposed research is to develop a mobile manipulator that can effectively learn impedance critical tasks by means of physical interactions with a human, and acquire human’s abilities via human-to-robot skill transfer for subsequent autonomous task execution. In a factory environment, execution of such tasks, e.g., drilling, screwing, are frequently encountered and can be easily accomplished by human workers. Nevertheless, automating these tasks with robots require expert robotics engineering knowledge, robot-specific arrangements in the factory, and exact model of the environment. Through the integration of human-to-robot skill transfer techniques, these monotonous tasks can be autonomously handled by a mobile manipulator so that human workers can focus on more complicated tasks. To this end, this project aims to develop required technologies to create such a system that can be actively used in a real factory environment for actual scenarios. With the successful completion of the project, a crucial building block will be built for human-centered robotic automation, which is of importance in keeping the manufacturing jobs in EU. Upon the completion of the project, it is anticipated that an invaluable robotic platform that corresponds to Industry 4.0 criteria will be obtained. Due to nature of the project, the system will be a patented end-product for industrial manufacturing tasks. Therefore, it will lead to a strong university-industry collaboration which will be greatly benefited by the host institute, OzU, and the researcher. Moreover, the project will greatly expand the research network for the researcher as he aims to be a leader in the field and expand his research expertise with this multidisciplinary project.

The recent catastrophic flood and landslide events triggered by heavy rainfalls have shown how vulnerable communities can be to natural disasters. To mitigate the impacts of natural disasters on communities, disaster resilience assessment and planning are required for the built-environment. The proposed research aims to develop a decision framework to support multi-hazard resilience of residential building stocks under rainfall-triggered floods and flow-type landslides (i.e., debris, mud-flows), considering two refinement levels in the framework: individual buildings vs. building portfolios in a community. The effects of uncertainties and spatial correlations in hazard demand and common building configurations and practices will be reflected in an aggregated assessment of multi-hazard resilience of building portfolios. The building portfolios that will be focused in the proposed methodology are residential buildings within a typical EU community, considering residential construction practice in Europe. However, the proposed framework can be adapted for resilience assessment and planning for other building portfolios involving different occupancies. The fellow Dr. Deniz, with her research experience in community disaster resilience and her firm-background in civil engineering, and reliability and statistical tools, has the required technical expertise to achieve the goal by conducting state-of-the-art robust analyses for the proposed project “A probabilistic decision framework for MULti-HAzard RESilience of residential building portfolios subjected to floods and landslides”. The proposed decision framework will greatly contribute to different stakeholders seeking to find optimal mitigation strategy for homes and to improve insurance portfolio risk policy, public policy and disaster management plans. This fellowship will support Dr. Deniz to establish an internationally well-recognized academic career and become one of the leading people on this particular research.