Drew Hanover

Papers

Total Citations

H-Index

About

Drew Hanover is a pioneering roboticist whose research lies at the intersection of aerial manipulation, multimodal locomotion, and autonomous systems. His work addresses critical challenges in enabling robots to operate seamlessly across diverse environments, from industrial infrastructure to complex terrains. Hanover’s most cited paper, "Perception-Aware Perching on Powerlines With Multirotors" (2022, 30 citations), introduces a novel framework that allows multirotor aerial robots to autonomously perch on powerlines for recharging, a key enabler for persistent infrastructure inspection. This work demonstrates his ability to combine perception, control, and mechanical design to solve real-world problems. More recently, in "Learning to Walk and Fly with Adversarial Motion Priors" (2024, 5 citations), Hanover tackles the grand challenge of robot multimodal locomotion, developing a learning-based approach that achieves smooth transitions between walking and flying. By leveraging adversarial motion priors, his method enables robots to adapt their gaits dynamically, pushing the boundaries of bio-inspired robotics. With a growing citation impact and a focus on practical, deployable solutions, Hanover is shaping the future of autonomous robots that can navigate and interact with the world in unprecedented ways.