Caio Cristiano Barros Viturino
Papers
3
Total Citations
28
H-Index
2
About
Caio Cristiano Barros Viturino is a robotics researcher whose work sits at the intersection of autonomous manipulation, path planning, and deep learning. His primary contributions focus on enhancing robotic grasping and motion control in cluttered, real-world environments. In his most cited work, "Adaptive Artificial Potential Fields with Orientation Control Applied to Robotic Manipulators" (2020, 21 citations), Viturino introduced a novel integration of adaptive potential fields with end-effector orientation control, enabling real-time, collision-free path planning for manipulators. He extended this framework in subsequent papers, including a 2021 study (5 citations) that combined convolutional neural networks with adaptive potential fields to create a complete 6D robotic grasping pipeline for autonomous pick-and-place in additive manufacturing. More recently, his 2023 work on selective 6D grasping using point clouds and RGB+D images (2 citations) addresses the computational challenge of 6D grasp generation, moving beyond the limitations of planar grasps. Viturino’s research is notable for bridging classical control theory with modern learning-based perception, making his systems both robust and practical for industrial automation. His work has clear implications for smart manufacturing and human-robot collaboration.
Research Focus
Key Achievements
Top Papers
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