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About

Anupa Sabnis is a robotics researcher whose work lies at the intersection of computer vision and autonomous navigation, with a particular focus on enabling mobile robots to perceive and move intelligently through their environments. Her research centers on visual homing—the ability of a robot to return to a home position using only visual cues—and depth estimation for robotic manipulation. Sabnis made significant contributions to robust steering control for autonomous homing, developing Lyapunov-based approaches that allow robots to navigate reliably under practical, real-world conditions. Her work on probabilistic methods for visual homing in the presence of dynamic obstacles addresses a key challenge in autonomous robotics: operating safely in unpredictable environments. She also advanced visual compass techniques, creating correlation-based methods using omnidirectional and multiple-camera views to help robots maintain orientation. Her most cited work, on single-image depth estimation for robotic applications (15 citations), demonstrates her ability to tackle fundamental perception problems. With over 47 total citations across her publications, Sabnis has established herself as a thoughtful contributor to the field of visual navigation, producing practical, theoretically grounded solutions that bring autonomous robots closer to reliable real-world deployment.