The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to significantly decrease the cost of environmentally friendly, new home construction. Currently, more than 1/6 of American households spend over half of their income on housing. This project is developing an artificial intelligence (AI)-based autonomous heavy-lift unmanned aerial vehicle (UAV) capable of building homes out of the cheapest, most abundant building material, earth. Such homes, referred to as adobe, are historically expensive due to high labor costs. However, the hhigh precision and versatility of AI-controlled UAVs enable autonomous construction that is cost-competitive and offers significant additional benefits, such as energy efficiency, fire resistance, and soundproofing.
This Small Business Innovation Research (SBIR) Phase I project will prototype an autonomous heavy-lift UAV capable of performing the individual tasks necessary to build the walls of a monolithic adobe structure with a novel robotic arm. For example, forming the adobe requires pushing a still-wet wall into the desired shape with a trowel. This force transfers to the UAV which must generate an equal-but-opposite force to maintain stability. No current UAV flight controller can handle these forces while maintaining stable flight. The company will use deep reinforcement learning to train a flight controller that can handle these and related forces while remaining in stable flight.
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.
