Martin Vetterli

École Polytechnique Fédérale de Lausanne

Papers

Total Citations

136

H-Index

About

Martin Vetterli is a pioneer in the intersection of signal processing, robotics, and computational sensing. His most influential work centers on using acoustic echoes for simultaneous localization and mapping (SLAM), a breakthrough demonstrated in his highly cited 2016 paper "EchoSLAM" (73 citations). This work showed how a robot with a collocated microphone and speaker could autonomously map an unknown room and localize itself purely from sound reflections—a paradigm shift from traditional vision- or lidar-based approaches. Vetterli also made foundational contributions to the theory of unlabeled sensing, solving the challenging problem of reconstructing signals when measurement order is unknown. His 2015 paper on this topic (35 citations) and its 2018 extension (10 citations) have become essential references for machine learning and data science. More recently, his 2022 work "Blind as a Bat" (18 citations) demonstrated practical audible echolocation on small robots, proving that low-cost audio hardware can enable robust obstacle detection and navigation. Vetterli’s research elegantly bridges theoretical signal processing with real-world robotic systems, showing that sound—often overlooked—can be a powerful sensing modality. His work has inspired a new generation of researchers to explore acoustic sensing for autonomous systems, earning him a reputation as a visionary in computational sensing and robotics.