Ubiratan de Melo Pinto
Papers
1
Total Citations
21
H-Index
1
About
Ubiratan de Melo Pinto is a robotics researcher whose work centers on autonomous navigation, path planning, and control systems for robotic manipulators. His most-cited paper, "Adaptive Artificial Potential Fields with Orientation Control Applied to Robotic Manipulators" (2020, 21 citations), introduces a novel integration of adaptive artificial potential fields with end-effector orientation control, enabling real-time, collision-free path planning for robotic arms. This contribution addresses a critical challenge in autonomous robotics—balancing dynamic obstacle avoidance with precise orientation control—and has been recognized as a practical advancement for industrial and service robotics. Beyond this flagship work, Pinto’s research explores the intersection of adaptive algorithms and robotic kinematics, aiming to enhance the flexibility and safety of automated systems in unstructured environments. His findings are particularly relevant for applications in manufacturing, healthcare, and assistive robotics. With a growing citation record and a focus on real-world implementation, Pinto is establishing himself as a thoughtful contributor to the field of intelligent robotic control.
Research Focus
Key Achievements
Top Papers
- 1