Daniel Marques
Papers
1
Total Citations
7
H-Index
1
About
Daniel Marques is a robotics researcher whose work centers on the optimization and design of high-redundancy robotic systems, with a particular focus on industrial automation. His most-cited paper, "Optimal automatic path planner and design for high redundancy robotic systems" (2019, 7 citations), addresses a critical challenge in manufacturing: the integration of robot arms with complex peripheral components like grippers, jigs, and external axes. Marques’s major contribution lies in developing automated path planning algorithms that optimize the configuration and movement of these multi-component robotic cells, reducing manual design effort and improving operational efficiency. His research bridges the gap between theoretical robotics and practical industrial deployment, offering solutions that enhance flexibility and reliability in automated production lines. While his citation count reflects a focused, early-career impact, Marques’s work is notable for its direct applicability to real-world manufacturing problems, making it valuable for engineers and researchers seeking to streamline robotic cell design. His approach underscores the importance of holistic system optimization in modern robotics.
Research Focus
Key Achievements
Top Papers
- 1