Dr. Garcia is actively
engaged in a diverse range of research activities within the realm of
autonomous vehicles and robots, encompassing experimental, theoretical, and
modeling and simulation work. His primary focus is developing advanced
algorithms for guiding and controlling various autonomous vehicles. With a
strong background in control engineering, he specializes in crafting
cutting-edge solutions for achieving optimal, robust, nonlinear, predictive,
and adaptive control in complex systems. Notably, Dr. Garcia is currently
delving into the fields of reinforcement learning to enhance robot maneuvering
capabilities and explore the integration of computer vision in the field of
artificial intelligence. Dr. Garcia was a control engineer and researcher in
FAU OME’s Knifebot project. He designed and tested optimal control laws,
including deep reinforcement learning, for an underwater biomimicking robot,
trajectory tracking, and fin kinematics. Dr. Garcia designed and tested deep
reinforcement learning for a spherical robot for position tracking during
his stay at PUCV and developed online algorithms for detecting, identifying,
and tracking persons in a train station based on AI computer vision. Dr. Garcia
designed flight control systems for fixed-wing and quadrotors, including robust
and optimal approaches.
