Mahmod Othman
Papers
1
Total Citations
2
H-Index
1
About
Mahmod Othman’s research focuses on advancing the precision and reliability of robotic systems, particularly Cable Driven Parallel Robots (CDPRs). His major contribution lies in integrating multiple computational algorithms—Modified Hough Transformation, Random Sample Consensus, and Linear Least Square—to extract the normal parameterization of straight lines from laser scanner data. This innovative approach offers a robust alternative to traditional camera-based or forward kinematics methods for determining platform position, addressing key limitations in accuracy and computational efficiency. While his most cited work has garnered 2 citations, its significance is underscored by its practical application in improving CDPR performance in real-world settings. Othman’s work exemplifies a hands-on, algorithmic approach to solving complex robotic localization problems, making him a notable figure in the field of robotics and automation. His research continues to inspire new methods for sensor integration and geometric extraction in robotic systems.
Research Focus
Key Achievements
Top Papers
- 1