Mohammadreza Kasaei
University of Edinburgh, University of Aveiro, Islamic Azad University, Isfahan, Informa (United Kingdom)
Papers
19
Total Citations
154
H-Index
7
About
Mohammadreza Kasaei is a robotics researcher whose work spans robot manipulation, grasping, and bipedal locomotion — two of the most challenging frontiers in embodied AI. His most influential contribution, "MVGrasp" (2022, 36 citations), introduced a real-time multi-view 3D grasping system capable of operating in highly cluttered environments, addressing a critical bottleneck for robots deployed in human-centered settings. Building on this, his work on simultaneous multi-view object recognition and grasping pushes robots toward truly open-ended, autonomous operation where perception and action are tightly integrated rather than treated in isolation. On the locomotion side, Kasaei has made sustained contributions to stable biped walking, developing closed-loop frameworks, omnidirectional walking engines for platforms like the NAO robot, and CPG-based locomotion strategies that draw inspiration from biological movement. His 2018 paper on optimal closed-loop humanoid walking has garnered 19 citations and remains a key reference in the field. More recently, his research has expanded into dynamic manipulation behaviors such as obstacle-aware object throwing, and data-efficient modeling of soft robots using non-parametric methods. Across more than a decade of output, Kasaei's work collectively advances the goal of creating robots that can reliably perceive, move, and interact within the complexity of real-world environments.
Research Focus
Key Achievements
Top Papers
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- 3Throwing Objects into A Moving Basket While Avoiding Obstacles13 citations · 2023
- 4A Fast and Stable Omnidirectional Walking Engine for the Nao Humanoid Robot12 citations · 2019
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- 7Instance-wise Grasp Synthesis for Robotic Grasping8 citations · 2023
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