Y. Pakzad
Papers
1
Total Citations
6
H-Index
1
About
Y. Pakzad is a robotics researcher whose work centers on improving autonomous navigation and localization for mobile robots, with a particular focus on omnidirectional platforms. His most-cited contribution, "An improvement of self-localization for omnidirectional mobile robots using a new odometry sensor and omnidirectional vision" (2004, 6 citations), addresses a critical challenge in mobile robotics: reducing positioning errors in 3-degree-of-freedom systems. Pakzad’s key innovation lies in integrating a modified odometry sensor with omnidirectional vision, employing a two-channel complementary filter to fuse these data streams. This approach significantly enhances self-localization accuracy for robots using three omni-wheels, a common design for agile, holonomic movement. By combining low-cost odometry with visual feedback, Pakzad’s work offers a practical, robust solution for real-world applications, from warehouse automation to service robotics. Though his citation count is modest, his research represents a foundational step in sensor fusion for omnidirectional robots, demonstrating how complementary filtering can overcome the limitations of individual sensors. For students and researchers exploring localization in non-holonomic or holonomic systems, Pakzad’s methodology provides a clear, implementable framework for achieving reliable, real-time positioning in dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1