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About

Luis Gracia is a robotics researcher whose work spans robot control, teleoperation, human-robot collaboration, and mobile robotics. He has made particularly significant contributions to the field of robotic surface treatment, developing sophisticated control frameworks that address the longstanding challenge of automating complex manual industrial tasks such as sanding, polishing, and deburring. His 2021 paper on augmented virtuality and haptic feedback-based teleoperation, which has garnered 107 citations, exemplifies his ability to bridge human dexterity with robotic precision. This work is complemented by a suite of highly cited 2018 studies introducing adaptive sliding mode control, admittance control, and hybrid position-force strategies for surface conditioning, collectively accumulating nearly 180 citations and establishing him as a leading voice in contact-driven robot manipulation. Beyond manipulation, Gracia has contributed foundational work in mobile robotics, including kinematic modeling of wheeled robots with slip and generic control frameworks applicable across robot platforms. His 2013 reactive sliding-mode collision avoidance algorithm further demonstrates his breadth, offering practical safety solutions for dynamic environments. His research on visual servoing with image delay compensation and human-robot collaboration for safe object transportation reflects a consistent commitment to making robotic systems both robust and practically deployable across diverse real-world settings.