Papers
27
Total Citations
321
H-Index
12
About
Marco Mendoza is a robotics and control systems researcher whose work spans robot manipulator control, vision-based systems, rehabilitation robotics, and parameter identification. His research consistently addresses the practical challenges of deploying intelligent robotic systems in real-world environments, particularly where exact system knowledge is unavailable or unreliable. Among his most influential contributions is a generalized PID-type control framework for robot manipulators operating under input constraints, which has garnered 40 citations and is notable for eliminating the need for precise system modeling — a significant practical advantage. Complementing this, his output-feedback extensions of PID-type schemes further democratize robust robot control design. Mendoza has also made substantial contributions to vision-based and impedance control strategies, combining calibration-free camera-space manipulation with interaction control to enable sophisticated path-tracking in industrial robots, with key papers attracting over 30 citations each. A distinctive dimension of his work is its humanitarian application: Mendoza has pioneered robot-assisted rehabilitation systems integrating haptic interfaces, augmented reality, and wave-based teleoperation for motor therapy, demonstrating both technical depth and social impact. His rigorous experimental evaluations of parameter identification methods on direct-drive robots further ground his theoretical contributions in verifiable practice, making his body of work essential reading for researchers in applied robotics and human-robot interaction.
Research Focus
Key Achievements
Top Papers
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- 5A vision-based, impedance control strategy for industrial robot manipulators18 citations · 2010
- 6A Dynamic-compensation Approach to Impedance Control of Robot Manipulators18 citations · 2010
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