FAU CA-AI Team Competes in DARPA Lift Challenge with Heavy-Lift Autonomous Aircraft Tuesday, Jun 16, 2026A team from the Center for Connected Autonomy and Artificial Intelligence (CA-AI), within Florida Atlantic University's College of Engineering and Computer Science, has been selected to compete in the Defense Advanced Research Projects Agency (DARPA) Lift Challenge, a national competition focused on advancing autonomous aerial logistics through next-generation aircraft design. The DARPA Lift Challenge is part of a long tradition of DARPA-led technology competitions that have influenced the trajectory of emerging industries. Most notably, DARPA's Grand Challenge and Urban Challenge competitions helped accelerate the development of autonomous vehicle technologies years before self-driving systems became commercially viable. Today, DARPA continues to use challenge-based innovation to advance critical technologies, with the Lift Challenge focused on expanding the capabilities of autonomous aviation and aerial logistics. "DARPA competitions have historically served as catalysts for technological breakthroughs, particularly in autonomous systems," said Dimitris Pados, Ph.D., director of CA-AI and Charles E. Schmidt Eminent Scholar Professor in the Department of Electrical Engineering and Computer Science. "For our students, participating in the Lift Challenge is an opportunity to engage with a problem at the forefront of aerospace innovation while applying the principles of autonomy, artificial intelligence, and engineering design that are central to CA-AI's research." Fully funded, organized, and supported by CA-AI, the project brings together seven FAU College of Engineering and Computer Science student researchers under the guidance of CA-AI faculty to design, build, and test heavy-lift autonomous tiltrotor aircraft for the competition. The DARPA Lift Challenge aims to advance autonomous flight capabilities by challenging teams to significantly increase the payload-to-weight performance of vertical-lift aircraft. Competitors are working toward a 4-to-1 payload-to-weight ratio, a benchmark that exceeds the capabilities of existing aircraft systems and represents a key milestone for future autonomous