SBIR Phase II: AI Generated Robotic Behavior

The broader impact of this Small Business Innovation Research (SBIR) Phase II project will be a domestic automation capability supporting future labor forces. The proposed work and innovation aim to enhance the scientific understanding of applying generative AI to minimize the technical skill needed to deploy new automation capabilities. This Small Business Innovation Research (SBIR) Phase II project addresses robotic manipulation of non-rigid materials for industrial automation. The primary research objective is to develop a generative AI stack optimized for deformable material handling, prioritizing execution speed and success rate in industrial settings. A secondary objective is to establish continuous learning methodologies that leverage on-premises production data to enable data-heavy initiatives to achieve superhuman performance. The research approach combines custom AI model development trained on rich operational datasets, experimental validation across multiple deformable material types, and implementation of continuous learning infrastructure for real-time model refinement. Anticipated results include validated proof-of-concepts demonstrating reliable task completion and a deployable system architecture enabling commercial-scale automation of deformable material handling tasks. 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.