Jordi Solsona

Universitat Ramon Llull, La Salle University

Papers

Total Citations

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About

Jordi Solsona is a researcher whose work sits at the intersection of robotics, computer vision, and neuromorphic computing. His primary research areas include autonomous mobile robot navigation, real-time visual processing, and the application of cellular neural networks (CNNs) to robotic systems. Solsona’s major contribution lies in demonstrating how CNNs—analog, parallel-processing architectures inspired by biological neural networks—can be harnessed to perform complex visual tasks such as feature detection and object recognition directly in hardware. This approach enables mobile robots to navigate and interpret their environment with minimal latency, bypassing the computational bottlenecks of traditional digital systems. His most-cited paper, "Guiding a mobile robot with cellular neural networks" (2002, 13 citations), showcases this breakthrough by proving that CNN-based vision can deliver real-time, on-board processing for autonomous guidance. Though his citation counts are modest, Solsona’s work is notable for its early and prescient integration of neural network hardware with mobile robotics, laying groundwork for later advances in edge AI and embedded computer vision. His research remains a touchstone for those exploring efficient, bio-inspired solutions for robotic perception.