Patricia Parlevliet

Papers

Total Citations

H-Index

About

Patricia Parlevliet is a pioneering researcher at the intersection of neuromorphic engineering and autonomous aerial systems. Her work focuses on developing bio-inspired sensing and control architectures that enable efficient, real-time decision-making for unmanned aircraft. Parlevliet’s most-cited paper, “Autonomous Flying With Neuromorphic Sensing” (2021, 9 citations), lays the groundwork for integrating event-driven vision sensors with flight control algorithms, drawing inspiration from the neural processing of flying insects. This contribution is critical for overcoming the power and latency constraints that limit current autonomous drones. By demonstrating how neuromorphic hardware can process visual information with microsecond precision, she has opened new pathways for lightweight, agile drones capable of navigating cluttered environments without heavy computational loads. Her research bridges neuroscience and robotics, advocating for interdisciplinary collaboration to make everyday autonomous flight a reality. Parlevliet’s work is particularly notable for its emphasis on policy and funding frameworks that support such convergence. As the field matures, her insights into neuromorphic sensing are poised to become foundational for next-generation autonomous aircraft, making her a key voice in the future of intelligent flight systems.