Dino Dominic Ligutan
Papers
4
Total Citations
34
H-Index
3
About
Dino Dominic Ligutan is a robotics researcher whose work focuses on intelligent control systems and robotic manipulation, particularly for assistive and hazardous environments. His key research areas include fuzzy logic control, artificial neural networks, and the design of robotic end-effectors and components using 3D printing. Ligutan’s most cited work (19 citations) presents a fuzzy logic-based joint controller for a 6-DOF robot arm integrated with machine vision feedback, enabling precise pick-and-place operations. He further advanced adaptive control by demonstrating an artificial neural network approach for a 4-DOF robotic arm intended for bomb disposal applications (9 citations). His contributions extend to mechanical design and analysis, including a modal and computational fluid dynamics study of a 3D-printed X-ray film handler for an assistant robotic system (4 citations), and the development of a novel three-claw robotic gripper end-effector (2 citations). Through these works, Ligutan has demonstrated a commitment to creating robust, adaptive, and practical robotic systems, with his research laying groundwork for safer human-robot interaction in critical tasks.
Research Focus
Key Achievements
Top Papers
- 1
- 2Adaptive Robotic Arm Control using Artificial Neural Network9 citations · 2018
- 3
- 4DESIGN OF A 3D-PRINTED THREE-CLAW ROBOTIC GRIPPER END-EFFECTOR2 citations · 2021