Agile Autonomous Technical Data Package to Path Robotic Task Specification

Here is a draft for a Direct to Phase II SBIR solicitation topic based on the technical capabilities of the data extraction and automated path-planning pipeline. The content has been carefully structured to be precise and concise while protecting all proprietary text.Direct to Phase II Topic DraftTopic ObjectiveObjective: Develop and demonstrate an automated, end-to-end software platform capable of ingesting heterogeneous Technical Data Packages (TDPs)—including 3D CAD models, 2D engineering drawings, Bills of Materials (BOMs), and textual specifications—to autonomously extract engineering intent and generate optimized, collision-free robotic inspection trajectories without manual waypoint programming or hard-coded scripting.The resulting system must bridge the gap between enterprise digital design data and physical automation by converting complex tolerances, geometric constraints, and manufacturing annotations into a standardized data model, simulating the execution in a physics-accurate virtual sandbox, and deploying executable inspection commands directly to physical mobile robotic manipulators. The objective is to drastically compress quality control programming timelines from days to under two hours and enable rapid robotic reconfiguration in highly agile manufacturing environments.Topic DescriptionBackground & Problem Statement: Modern aerospace manufacturing and sustainment pipelines face severe bottlenecks due to legacy quality control (QC) practices. As defense systems shift toward highly modular, rapidly evolving, and low-cost attritable architectures, traditional fixed automation becomes commercially and operationally impractical. Traditional robotic inspection lines require highly specialized programmers to manually teach waypoints, configure physical sensor triggers, and execute tedious trial-and-error collision testing on vendor-specific offline programming utilities. This labor-intensive paradigm introduces severe production delays, as errors or dimensional variations are often caught late in the assembly stream, resulting in compounding downstream costs and extended lead times.While digital enterprise structures routinely house complete engineering intent within comprehensive Technical Data Packages (TDPs)—complete with 3D geometry, Geometric Dimensioning and Tolerancing (GD&T) markers, material specifications, and assembly metadata—translating this multi-format data into actionable instructions remains a manual and error-prone process. To meet the demand for rapid production scaling and point-of-need deployment, the Department of the Air Force requires an intelligent software layer that dynamically parses TDP data and translates it directly into autonomous robotic execution paths.Phase II Expected Outcomes: Proposers responding to this Direct to Phase II topic must demonstrate a mature conceptual foundation, such as completed preliminary software blocks or data-parsing prototypes originally validated under related early-stage research. Phase II efforts must deliver a hardened, end-to-end software prototype validated against representative aerospace assembly geometries.Key technical deliverables include the ingestion/planning software, documentation for enterprise data interfaces, and localized simulation proof-of-concepts. The system performance will be benchmarked against key parameters, targeting a setup time reduction to under 8 hours for novel manufacturing configurations and compressing numerical programming timelines down to less than 1.5 hours. Final validation should culminate in a software-driven execution demo using either high-fidelity simulations or physical manufacturing hardware within a pilot production framework.