I-Corps: Translation Potential of a Software Platform for Optimizing Collaborative Human-Robot Operations

The broader impact of this I-Corps project is based on the development of an autonomous mobile robot (AMR) platform for collaborative internal logistics and material handling tasks. This technology has the potential to enable efficient and scalable adoption of collaborative human-mobile robot operations for supply chain logistics. The competitiveness of U.S. manufacturing and service sectors, particularly in industries of national importance such as semiconductors, transportation, and retail, depends on supply chains that are efficient, resilient, and adaptive to dynamic demands. As supply chain operations increasingly rely on collaborative ecosystems that combine human expertise with AMR capabilities, improving safely and efficiently managing multiple AMRs. This project optimizes collaborative human-mobile robot operations, empowering fulfillment managers, logistics planners, and supply chain coordinators to streamline operations in manufacturing, warehousing, and transportation. By addressing critical market needs, the technology could enhance U.S. economic competitiveness and strengthen the supply chain workforce. Additionally, its broader impact lies in fostering innovation, improving workplace efficiency, and creating opportunities for workforce upskilling in industries critical to national growth and sustainability.

This I-Corps project utilizes experiential learning coupled with first-hand investigation of the industry ecosystem to assess the translation potential of the technology. The solution is based on the development of a cloud-based autonomous mobile robot (AMR) orchestration platform that can effectively plan, monitor, and optimize collaborative human-mobile robot operations performing material handling tasks. The technology will advance human-robot operations by facilitating real-time coordination of human-robot systems for responsive and resilient workflows. To ensure safe and efficient AMR orchestration, the technology leverages novel artificial intelligence (AI)-powered algorithms that account for real-world complexities and operational uncertainties. Initial results highlight the technology’s potential to improve fulfillment speed in warehouse logistics while providing actionable insights into AMR orchestration to overcome existing challenges. The AMR orchestration platform could offer a transformative approach to optimizing human-mobile robot collaboration, driving efficiency, and supporting adaptable, scalable solutions in supply chain intralogistics operations.

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.

Award Number: 2447357
Principal Investigator: Sharan Srinivas
Funds Obligated: $50,000
State: MO