Hossein Jahandideh
Papers
1
Total Citations
6
H-Index
1
About
Hossein Jahandideh is a roboticist whose work rethinks foundational assumptions in robot dynamics and control. His research centers on parameter estimation, system identification, and optimization-based methods for robotic systems. In his highly cited 2012 paper, "Use of PSO in Parameter Estimation of Robot Dynamics; Part One: No Need for Parameterization," Jahandideh introduced a novel approach that eliminates the traditional requirement for parameterization—the process of finding the minimum set of dynamic parameters. By leveraging Particle Swarm Optimization (PSO), his method enables offline parameter estimation directly from the full dynamic model, bypassing complex symbolic simplifications. This contribution simplifies and generalizes the identification of robot inertial parameters, offering a practical alternative for researchers and engineers working with high-degree-of-freedom manipulators. With 6 citations, this work has influenced subsequent studies in evolutionary optimization for robotics. Jahandideh’s research bridges theoretical rigor and computational intelligence, providing tools that make robot modeling more accessible and robust. His work continues to inspire advances in adaptive control and real-time system identification.
Research Focus
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Top Papers
- 1