Pablo Malvido Fresnillo
Papers
7
Total Citations
59
H-Index
4
About
Pablo Malvido Fresnillo is a robotics researcher whose work sits at the intersection of machine vision, industrial manipulation, and human-robot interaction. His primary research areas include deformable object manipulation, bimanual robotic control, and the development of open-source software frameworks for ROS-based systems. Fresnillo’s most cited paper, “Machine Vision and Robotics for Primary Food Manipulation and Packaging: A Survey” (19 citations), provides a comprehensive overview of how vision and robotic technologies are transforming quality control in the food industry. He has also made significant contributions to extending the MoveIt motion planning framework for advanced industrial applications (15 citations) and to creating reconfigurable user interfaces for complex ROS systems (9 citations). His work on bimanual manipulation of deformable linear objects, such as cable routing (6 citations), addresses a notoriously difficult challenge in automation. Additionally, Fresnillo has advanced programming by demonstration methods to make robotic systems more accessible to non-experts (4 citations). His research on tactile sensing for deformable object grasping (3 citations) further demonstrates his commitment to bridging the gap between academic robotics and practical industrial needs. With a growing citation record and a focus on real-world applications, Fresnillo is establishing himself as a key contributor to the future of flexible and intelligent robotic automation.
Research Focus
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Top Papers
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