Hasan Danaci
Papers
2
Total Citations
19
H-Index
2
About
Hasan Danaci is an emerging researcher specializing in robotics and computational intelligence, with a particular focus on solving complex kinematic problems in serial robot manipulators. His work centers on applying metaheuristic optimization techniques — most notably Particle Swarm Optimization (PSO) — to address the inverse kinematics problem, a foundational challenge in manipulator robotics that involves calculating precise joint angles to achieve desired end-effector positions and orientations. Danaci's most notable contributions include two closely related studies that demonstrate the effectiveness of PSO as an alternative to traditional analytical and numerical methods for inverse kinematics solutions. His 2023 paper advances this work further by incorporating POSIX Threads implementation, enabling parallel computation and improving real-time performance — a critical consideration for practical robotic applications. Together, these papers have accumulated nearly 20 citations, signaling growing recognition within the robotics research community. His research is particularly valuable for students and engineers working on robotic arm control systems, as it bridges the gap between theoretical optimization algorithms and practical implementation strategies. Danaci's trajectory suggests a promising career at the intersection of artificial intelligence and robotics engineering.
Research Focus
Key Achievements
Top Papers
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