STTR Phase I: Subcanopy 3D forest mapping by uncrewed aerial vehicle

Morphobotics Llc, Barrington RI

Investigators

Abstract

The broader/commercial impact of this Small Business Technology Transfer (STTR) Phase I project is a tool to help mitigate the wildfire crisis in the western United States. Prescribed burns are one of the most effective ways to prevent the uncontrolled, large-scale wildfires that devastate entire ecosystems, communities, and economies, but the environmental assessment required for burns may delay the burn by months or years due to overburdened agencies. The innovation addresses this pain point with an automated survey solution, reducing both the paperwork burden and the potential for error in burn area vegetation mapping and spatial fire modeling. The solution ensures that prescribed burn plans use the best available vegetation data, providing fire managers with an accurate prediction of expected fire behavior for determining control strategy, staffing, and resources. This innovation would be the first automated prescribed burn spatial fire modeling solution using an autonomous Unmanned Aerial Vehicle (UAV). This innovation meets the STTR program’s focus on unproven, high-impact innovations because sub-canopy mapping by UAV is a cutting-edge application of autonomous flight, with challenges in optimization and decision-making. The application of UAV technology to prescribed burn environmental assessments will help to address the growing wildfire crisis in the United States by reducing the delay between the decision to burn at a selected site and the execution of the burn. The technical hurdles to be addressed by the proposed project include both real-time, sub-canopy 3D mapping and optimization for constraints across sensor requirements, cluttered environment exploration, and SWAP (size, weight, and power) limitations. The goals are to produce a high-fidelity, open-source. UAV exploration environment, to implement 3D mapping on a resource-constrained computer that meets UAV payload requirements, to incorporate species-specific decision-making criteria into the UAV exploration algorithm, and to conduct validation testing to verify technical and early commercial feasibility. To achieve these goals, the development plan includes a series of milestones following a test-driven, development project management strategy, including simulation testing (software in the loop), tabletop testing (hardware in the loop), and field tests. 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.