Papers
7
Total Citations
267
H-Index
5
About
David Ricardo Cruz is a leading researcher in robotics and nonlinear control systems, with a focus on enhancing the precision and energy efficiency of robotic manipulators. His seminal work on the "Novel Nonlinear Hypothesis for the Delta Parallel Robot Modeling" (76 citations) introduced innovative bounded-map approaches to improve dynamic modeling, while his "Optimization of Sliding Mode Control to Save Energy in a SCARA Robot" (58 citations) advanced robust control techniques for industrial automation. Cruz also made significant contributions to localization with his "Indoor Robot Positioning Using an Enhanced Trilateration Algorithm" (52 citations), enabling accurate factory-floor navigation. His research on stabilizing robots under actuator nonlinearities using sigmoid-mapping regulators (47 citations) and cascade control strategies for self-balancing vehicles (28 citations) demonstrates his versatility across mobile and surgical robotics. With over 250 total citations, Cruz's work bridges theoretical control theory and practical robotic applications, including minimally invasive surgery. His achievements highlight a commitment to developing intelligent, energy-saving automation solutions that address real-world industrial and medical challenges.
Research Focus
Key Achievements
Top Papers
- 1Novel Nonlinear Hypothesis for the Delta Parallel Robot Modeling76 citations · 2020
- 2Optimization of Sliding Mode Control to Save Energy in a SCARA Robot58 citations · 2021
- 3Indoor Robot Positioning Using an Enhanced Trilateration Algorithm52 citations · 2016
- 4Stabilization of Robots With a Regulator Containing the Sigmoid Mapping47 citations · 2020
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