Rafael Herguedas
Papers
8
Total Citations
108
H-Index
6
About
Rafael Herguedas is a robotics researcher whose work sits at the intersection of multi-robot systems, deformable object manipulation, and autonomous control. His research addresses one of the field's most technically demanding challenges: enabling teams of robots to reliably grasp, transport, and reshape deformable objects — tasks with far-reaching implications for industrial automation, healthcare, and logistics. His most influential contribution, a comprehensive 2019 survey on multi-robot manipulation of deformable objects (65 citations), established a foundational reference for the community by systematically mapping the landscape of modeling, perception, planning, and control challenges in this domain. Building on this groundwork, Herguedas developed novel formation controllers that simultaneously manage shape control and object transport, incorporating collision avoidance and double-integrator dynamics to handle real-world complexity with greater precision and safety. A recurring theme across his work is scalability — designing control frameworks that remain robust as robot teams grow and object behaviors become less predictable. His more recent investigations into control barrier functions and adaptive Bayesian optimization reflect a commitment to bridging theoretical rigor with practical deployment. Collectively, his publications have attracted over 100 citations, marking him as an emerging and productive voice in autonomous robotic manipulation research.
Research Focus
Key Achievements
Top Papers
- 1Survey on multi-robot manipulation of deformable objects65 citations · 2019
- 2Simultaneous shape control and transport with multiple robots15 citations · 2020
- 3Multirobot Transport of Deformable Objects With Collision Avoidance7 citations · 2022
- 4
- 5Multi-camera coverage of deformable contour shapes6 citations · 2019
- 6
- 7Manipulation of Deformable Objects with a Multi-robot System1 citations · 2024
- 8