Sergio Morales

Papers

Total Citations

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About

Sergio Morales is a robotics researcher whose work bridges the gap between classical control theory and modern machine learning, with a primary focus on mobile robotics and soft robotic systems. His most influential contribution, "LQR Trajectory Tracking Control of an Omnidirectional Wheeled Mobile Robot" (2018), has garnered 26 citations and addresses critical challenges in wheeled mobile robot (WMR) navigation—a field with growing applications in agriculture, mining, and industry. By applying Linear Quadratic Regulator (LQR) control to omnidirectional platforms, Morales advanced the understanding of holonomic locomotion and precise trajectory tracking. More recently, his 2022 work, "Dynamic Modeling of a Soft Laparoscope: A Deep Neural Network Approach," introduces an innovative data-driven methodology for modeling soft robots, which are notoriously difficult to characterize due to their diverse designs and complex deformations. By leveraging deep neural networks, Morales simplifies the modeling process, connecting essential variables for task execution in surgical contexts. Though early in its citation impact, this work represents a significant step toward practical, model-free control of soft medical devices. Morales’ research demonstrates a clear trajectory from foundational control theory to cutting-edge applications in soft robotics, positioning him as a versatile contributor to both industrial automation and minimally invasive surgical technologies.