Dominic Reber

École Polytechnique Fédérale de Lausanne

Papers

Total Citations

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About

Dominic Reber is a robotics researcher whose work centers on tactile sensing, in-hand manipulation, and the predictive modeling of object dynamics. His key contributions lie at the intersection of tactile and audio data, where he develops robust methods for estimating forces and anticipating the motion of objects with movable internal contents—a critical challenge for dexterous robotic hands. In his most cited work, "A Predictive Model for Tactile Force Estimation Using Audio-Tactile Data" (2023), Reber addresses the difficulty of quickly estimating object dynamics to compensate for internal torques during manipulation. This research is foundational for enabling robots to handle everyday objects, such as containers with shifting liquids or loose parts, with greater precision and stability. Though early in his career, with 4 citations on this paper, his work has already garnered attention for its innovative fusion of tactile and auditory feedback. Reber’s contributions are paving the way for more adaptive and responsive robotic systems, making him a promising voice in the field of robotic manipulation and sensorimotor control.