Adrien Hoffet

École Polytechnique Fédérale de Lausanne

Papers

Total Citations

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About

Adrien Hoffet is pioneering the use of audible sound for robotic perception, drawing inspiration from biological echolocation. His most-cited work, "Blind as a Bat: Audible Echolocation on Small Robots" (2022, 18 citations), introduces a novel approach that enables small robots to detect obstacles, localize themselves, and map their environment using only standard microphones and speakers—sensors already present on most platforms. This work challenges the dominance of vision and LiDAR in robotics, offering a low-cost, lightweight alternative for safe autonomous navigation. Hoffet’s key research areas span bio-inspired robotics, audio signal processing, and sensor fusion, with a focus on making perception accessible for resource-constrained robots. By demonstrating that audible echolocation can be practical for real-world deployment, he opens new avenues for robots operating in dark, dusty, or visually cluttered environments. His contributions are particularly impactful for swarm robotics and education, where simplicity and affordability are paramount. With this foundational paper already garnering attention, Hoffet is establishing himself as a leading voice in the emerging field of audio-based robotic perception.