Victor Hugo Soto-Herrera

Instituto Tecnológico de Querétaro, Tecnológico de Monterrey

Papers

Total Citations

H-Index

About

Victor Hugo Soto-Herrera is a rising researcher at the forefront of human–robot collaboration, specializing in the integration of deep learning with collaborative robotics (cobots) for advanced manufacturing and assembly tasks. His work addresses the critical need for more intuitive, adaptable, and user-friendly interactions between humans and machines on the factory floor. Soto-Herrera’s major contributions include pioneering frameworks that combine real-time hand tracking with cobot control, enabling flexible, natural, and safe human-robot interaction without the need for traditional programming interfaces. His most cited paper, “Integration of Deep Learning and Collaborative Robot for Assembly Tasks” (2024), has already garnered 24 citations, underscoring its timely impact on the field. In a complementary study, “Flexible Human-Robot Interaction: Collaborative Robot Integrated with Hand Tracking” (2023), he proposed novel methods to enhance cobot responsiveness and user accessibility. By bridging deep learning and physical robotics, Soto-Herrera is helping shape the next generation of smart, cooperative manufacturing systems, making him a notable voice in the evolving landscape of Industry 4.0 and human-centered automation.