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About

Wouter Jansen is a robotics and sensor systems researcher whose work sits at the intersection of acoustic sensing, autonomous navigation, and machine learning. He has made notable contributions to the development of in-air sonar technology, advancing low-cost MEMS microphone array systems capable of real-time 3D acoustic imaging for mobile robotics applications. His embedded sensor platform, eRTIS, demonstrates practical deployment of these systems in real-world robotic scenarios including obstacle avoidance and corridor following. Jansen's research extends into autonomous localization and mapping, with his LatentSLAM work leveraging unsupervised multi-sensor representation learning to address perceptual aliasing challenges that limit biologically inspired SLAM approaches like RatSLAM. His more recent work pushes further into deep learning territory, with EchoPT applying pretrained transformer architectures and predictive coding principles to sonar-based perception — a novel fusion of neuroscience-inspired computation and acoustic robotics. He has also contributed to MIMO virtual array techniques for radial velocity estimation of multiple objects using in-air sonar. With his most-cited work accumulating citations across venues in sensor networks, robotics, and computer vision, Jansen represents a growing voice in the emerging field of acoustic machine perception for autonomous systems.