IRES: Advancing Research on Optimizing Collaborative Human-Mobile Robot Operations for Next-Generation Manufacturing and Service Systems

This IRES project prepares U.S. students to address future supply chain challenges in manufacturing and service systems by exploring how humans and autonomous mobile robots can collaborate effectively in shared workspaces. In response to increasing automation across industries, students engage in hands-on research to design, optimize, and manage collaborative systems for real-world tasks such as hospital intralogistics, semiconductor manufacturing, and warehouse order picking. Germany, a global leader in Industry 4.0, ranks among the highest in industrial robot adoption, making it an ideal setting for research on collaborative automation. The University of Passau in Germany, serving as the host institution, offers a premier research environment with strengths in decision science, human-robot interaction, and optimization, supported by strong academic programs and industry partnerships. By working directly with German faculty and collaborators, students gain international experience while contributing to innovations essential for next-generation smart supply chains. Through cross-cultural engagement, industry site visits, and sustained mentorship, participants develop a global outlook, strengthen their analytical and technical skills, cultivate a passion for advanced careers, and contribute to building a globally competitive STEM workforce in areas of national importance. This project addresses both fundamental and applied research challenges in Collaborative Human-Mobile Robot Operations (CHROps), a critical area for advancing human-centered automation in next-generation supply chains. Students engage with use-inspired problems across strategic, tactical, and operational levels, including the coordination of human–robot teams in dynamic environments, cost-effective fleet sizing under uncertainty, and facility layout redesign for safe and efficient collaboration. The program prepares students to (i) develop mathematical models and AI-powered algorithms, (ii) implement and evaluate solutions using digital twin platforms, and (iii) formulate interdisciplinary frameworks for CHROps design, operations and management. Research activities are organized into three phases: pre-departure technical and cultural preparation, immersive research at the University of Passau in Germany, and post-research synthesis and dissemination in the United States. The project advances theories, algorithms, and modeling frameworks for CHROps and promotes interdisciplinary approaches to drive future innovations in collaborative automation across critical sectors. A structured evaluation process assesses student development and program impact across all phases, informing continuous refinement of the training experience. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.