Marco Moran-Armenta

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About

Marco Moran-Armenta is a rising force in robotics control, specializing in the trajectory tracking and teleoperation of complex mobile systems. His research masterfully bridges classical control theory with modern artificial intelligence, focusing on skid-steering mobile robots and robot manipulators. In his highly cited 2023 work, Moran-Armenta developed a rigorous input-output linearization-based controller for skid-steering robots, providing a formal closed-loop stability analysis using perturbed systems theory—a foundational contribution that has already garnered 11 citations. He further advances the field by integrating neural network compensation with PID control for robot manipulator trajectory tracking (2025, 6 citations), demonstrating how AI can enhance traditional control robustness. Most notably, his 2025 work tackles the formidable challenge of bilateral teleoperation of skid-steering robots under time-varying delays, proposing a novel neural network-based controller that ensures accurate leader-follower coupling. By systematically combining kinematic control, nonlinear analysis, and neural compensation, Moran-Armenta is establishing himself as a key innovator in making autonomous and teleoperated robots more reliable and responsive in real-world applications.