Perception & Representation
This pillar addresses how robots can transform raw tactile and visuo-haptic signals into meaningful representations of contact, shape, compliance, and interaction dynamics. I am interested in perception methods that help robots understand not only what they touch, but also how objects and surfaces behave under contact, building toward more robust and transparent interaction in unstructured environments. In the spirit of embodied intelligence, this work connects sensing, representation learning, and task-relevant understanding to support dexterous manipulation and real-world autonomy.
A major open problem is how to build representations that generalize across sensors, tasks, and domains while remaining interpretable enough to support debugging, adaptation, and trust. Current work explores cross-modal learning, latent alignment, sensor transfer, and representations that preserve the structure of physical contact. I am particularly interested in methods that make tactile perception more data-efficient, more robust under distribution shift, and more useful in settings where robots must operate safely and transparently alongside people.
Related Projects
Featured Publications:
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SPLIT: Separating Physical-Contact Via Latent Arithmetic in Image-Based Tactile Sensors
Robotics and Autonomous Systems. vol. 203, pp. 105498. Sep 2026. Zai El Amri, Wadhah; Navarro-Guerrero, Nicolás
DOI, PDF, URL, bib file. bibkey: ZaiElAmri2026SPLIT Supplementary material ©2026 The Authors. -
Vibro-Sense: Robust Vibration-based Impulse Response Localization and Trajectory Tracking for Robotic Hands
Under Review in Robotics and Autonomous Systems. pp. 1-13. Jan 2026. Zai El Amri, Wadhah; Navarro-Guerrero, Nicolás
DOI, PDF, URL, bib file. bibkey: ZaiElAmri2026VibroSense Supplementary material ©2026 The Authors. -
Advances in Compliance Detection: Novel Models Using Vision-Based Tactile Sensors
IEEE International Conference on Development and Learning (ICDL). pp. 1-8. Prague, Czech Republic. Sep 2025. Li, Ziteng; Kuhlmann, Malte; Nisky, Ilana; Navarro-Guerrero, Nicolás
DOI, PDF, URL, bib file. bibkey: Li2025Advances Supplementary material ©2025 The Authors. -
ACROSS: A Deformation-Based Cross-Modal Representation for Robotic Tactile Perception
IEEE International Conference on Robotics and Automation (ICRA). pp. 5836-5842. Atlanta, GA, USA. May 2025. Zai El Amri, Wadhah; Kuhlmann, Malte; Navarro-Guerrero, Nicolás
DOI, PDF, URL, bib file. bibkey: ZaiElAmri2025ACROSS Supplementary material ©2025 IEEE The Authors. -
Vibro-Sense: A Bio-Inspired Vibration-Based Tactile Sensor for Robotics
German Robotics Conference (GRC). pp. 1-3. Nuremberg, Germany. Mar 2025. Zai El Amri, Wadhah; Faúndes-Tejos, Nicolás; Navarro-Guerrero, Nicolás
PDF, bib file. bibkey: ZaiElAmri2025VibroSense ©2025 The Authors. -
Toward Vision-Based Object Compliance Estimation
German Robotics Conference (GRC). pp. 1-3. Nuremberg, Germany. Mar 2025. Kuhlmann, Malte; Li, Ziteng; Navarro-Guerrero, Nicolás
PDF, bib file. bibkey: Kuhlmann2025VisionBased ©2025 The Authors. -
Transferring Tactile Data Across Sensors
40th Anniversary of the IEEE Conference on Robotics and Automation (ICRA). pp. 1540-1542. Rotterdam, The Netherlands. Sep 2024. Zai El Amri, Wadhah; Kuhlmann, Malte; Navarro-Guerrero, Nicolás
DOI, PDF, URL, bib file. bibkey: ZaiElAmri2024Transferring ©2024 IEEE The Authors. -
Optimizing BioTac Simulation for Realistic Tactile Perception
International Joint Conference on Neural Networks (IJCNN). pp. 1-8. IEEE World Congress on Computational Intelligence (IEEE WCCI). Yokohama, Japan. Jul 2024. Zai El Amri, Wadhah; Navarro-Guerrero, Nicolás
DOI, PDF, URL, bib file. bibkey: ZaiElAmri2024Optimizing Supplementary material ©2024 IEEE The Authors. -
A Biomimetic Fingerprint for Robotic Tactile Sensing
International Symposium on Robotics (ISR Europe). pp. 112-118. Stuttgart, Germany. Sep 2023. Juiña Quilachamín, Oscar Alberto; Navarro-Guerrero, Nicolás
DOI, PDF, URL, bib file. bibkey: JuinaQuilachamin2023Fingerprint Supplementary material ©2023 The Authors. -
AU Dataset for Visuo-Haptic Object Recognition for Robots
figshare. Jun 2021. Bonner, Lasse Emil R.; Buhl, Daniel Daugaard; Kristensen, Kristian; Navarro-Guerrero, Nicolás
DOI, PDF, URL, bib file. bibkey: Bonner2021AU ©2021 CC BY 4.0 The Authors. -
Evaluating Integration Strategies for Visuo-Haptic Object Recognition
Cognitive Computation. vol. 10, no. 3, pp. 408–425. Jun 2018. Toprak, Sibel; Navarro-Guerrero, Nicolás; Wermter, Stefan
DOI, PDF, URL, bib file. bibkey: Toprak2018Evaluating Supplementary material ©2018 Springer US The Authors.