Rodrigo Zenha

Queen Mary University of London, University of Lisbon

Papers

Total Citations

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About

Rodrigo Zenha is a leading researcher in robotic tactile perception and manipulation, specializing in how robots can use touch to understand and interact with their environment. His work bridges the gap between structured laboratory settings and real-world unstructured scenarios, focusing on three key areas: tactile object recognition, adaptive body schema learning, and slip detection. In his highly cited 2022 study, Zenha demonstrated that dynamic exploratory procedures significantly outperform single-touch methods for robotic object recognition, a finding that has garnered 16 citations and reshaped how robots gather tactile information. His 2018 paper on incremental body schema adaptation, with 14 citations, introduced a novel framework for robots to continuously update their internal body representation based on touch events—a critical step toward more autonomous and self-aware robotic systems. Zenha’s 2021 work on tactile slip detection, leveraging distributed sensing of both normal and shear forces, achieved 7 citations by addressing the persistent challenge of detecting object slippage in uncontrolled environments. Together, these contributions establish Zenha as a pioneer in making robotic touch more robust, adaptive, and practical for real-world applications, from industrial automation to assistive robotics.