SBIR Phase I: AI Generated Robotic Behavior

Award ID: 2404534

The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be an expanded automation capability and adaptive future labor force. Robotic automatic technology requires systems integrators and engineers to predict and account for every system detail, from motion planning to obstacle detection and avoidance. For example, many automation attempts have yet to scale due to the rapidly increasing costs of a high-mix, high-SKU business model. Cost-effective deployment of robotic automation systems is critical to economic success. The proposed work and innovation aim to enhance the scientific understanding of applying generative AI to minimize the skill to deploy new automation capabilities. The proposed solution is expected to automate specific repetitive labor tasks in the near term, with potential applications across various labor challenges. The proposed solution will increase productivity, improve safety, and transform the nature of our future workforce. The technology is expected to drive competitive economics in various labor markets, including enabling domestic manufacturing to be more economically viable. This Small Business Innovation Research (SBIR) Phase I project will advance generative AI technologies to address new types of robotic control previously too expensive or impossible with conventional methods. The proposed R&D will focus on advancing and developing new solutions for non-rigid materials and environments, an area of labor that is underserved by current robotic technologies. In Phase 1, the company proposes to build a robust system to demonstrate the feasibility and capability of the proposed AI system and cross-experimentation against best-in-class imitation learning techniques. The project will also include experimentation and development of novel AI model architectures to better address the unique requirements of the problem. Once developed, the advanced robotic control technology is anticipated to help address many repetitive, dull, dirty, and dangerous tasks that are faced across various domestic industries. This includes creating high-value jobs and a more robust and independent domestic labor capability. 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.

NSF Program Director: Peter Atherton