Papers

3

Total Citations

5

H-Index

2

About

Sara Hosseini’s research lies at the intersection of robotics, motion planning, and energy efficiency, with a particular focus on industrial robot arm manipulators. Her work addresses critical challenges in automation, including kinodynamic motion planning, inverse kinematics, and energy consumption estimation. In her 2020 paper, she introduced a novel cost function formulation for energy-efficient motion planning of a 2-DOF robot arm, modeling inertia, Coriolis, centrifugal, and friction losses to optimize performance. Her 2017 contribution provided an explicit inverse kinematic solution for the FUM 6R-20 articulated arm using a dual quaternion approach, a key advancement for six-axis robots developed at Ferdowsi University of Mashhad Robotics Lab. Most recently, in 2024, Hosseini proposed a method for estimating energy consumption during trajectory planning for a 6-DoF UR3e robot, directly supporting human-robot collaborative scheduling in modern manufacturing. Though her citation counts are currently modest, her work lays foundational groundwork for energy-aware robotics and industrial automation. Hosseini’s research is particularly relevant for students and engineers seeking to reduce energy footprints in robotic systems while maintaining precision and efficiency.

Research Focus

Key Achievements

2
H-Index
3
Papers
5
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Kinodynamic Motion Planning and Energy Loss Cost Function Modelling for a 2- DOF Robot Arm Manipulator
2 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Friedrich-Alexander-Universität Erlangen-Nürnberg, Tabaran Institute of Higher Education

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago