Jorge Igual

Papers

Total Citations

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About

Jorge Igual is a leading researcher in the intersection of robotics, control systems, and machine learning, with a primary focus on bipedal locomotion and gait stability. His major contributions center on developing predictive algorithms to ensure the safe and stable walking of biped robots and exoskeletons. Specifically, Igual pioneered the Predicted Step Viability (PSV) algorithm, a sophisticated multi-step optimization criterion that assesses the stability of future steps before they are executed. By transforming this complex planning problem into a real-time classification task, his work enables robots to proactively predict and avoid falls, a critical challenge in humanoid robotics. His most cited papers, including "Time Series Classification for Predicting Biped Robot Step Viability" and "Biped Gait Stability Classification Based on the Predicted Step Viability," each garnering 2 citations, lay the groundwork for safer, more autonomous bipedal machines. Igual’s research is instrumental for advancing assistive technologies like exoskeletons and for creating more resilient humanoid robots, directly impacting fields from rehabilitation engineering to autonomous navigation.