Henrique B. Garcia

Universidade Federal de São Carlos, Universidade de São Paulo

Papers

Total Citations

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About

Henrique B. Garcia is a robotics researcher whose work bridges classical control theory and modern machine learning, with a focus on enhancing robot-environment interaction. His primary research areas include impedance control, force control algorithms, and reinforcement learning for autonomous systems. Garcia's most significant contribution lies in advancing the practical implementation of impedance control for industrial robots, as detailed in his highly cited 2016 paper (10 citations), which systematically compares algorithms for simulating and applying this force control technique—a cornerstone of modern robotics for tasks requiring delicate contact. He further refined this work in 2017 (5 citations) by introducing a genetic algorithm to optimize the dynamic coupling between a robot and its environment, enabling more adaptive and robust tool-part contact. Demonstrating his versatility, Garcia has also explored deep reinforcement learning, developing an agent for an autonomous wheeled rover that combines visual and dynamics sensing to navigate noisy GPS conditions (2019, 2 citations). While his citation counts reflect a focused, early-career impact, his contributions are foundational for researchers and engineers seeking to implement safe, responsive robotic systems in both industrial and academic settings.