Mohammadreza Yavari
Papers
2
Total Citations
28
H-Index
2
About
Mohammadreza Yavari is a roboticist whose research lies at the intersection of aerial manipulation, optimal control, and kinodynamic motion planning. His work focuses on enabling autonomous systems—particularly rotary-wing UAVs equipped with manipulators—to perform complex tasks with greater efficiency and safety. In his highly cited 2018 paper on a pitch-hover UAV with a two-link manipulator, Yavari introduced an optimal real-time trajectory control strategy that not only ensures stable in-place hovering but also extends flight time through energy-optimal coordination. This contribution addresses a critical challenge in Unmanned Aerial Manipulators (UAMs), where redundancy and holonomy must be balanced against limited onboard power. Building on this, his 2019 work on "Lazy Steering RRT*" advanced the field of kinodynamic motion planning by integrating a neural network to bypass computationally expensive steering function iterations, achieving asymptotically optimal paths for constrained nonlinear systems without sacrificing exploration efficiency. With over 28 citations across these two flagship papers, Yavari’s work has influenced both the theoretical foundations of sampling-based planning and the practical deployment of aerial robots in inspection, logistics, and search-and-rescue operations. His innovative fusion of control theory, optimization, and machine learning continues to shape the next generation of autonomous aerial manipulators.
Research Focus
Key Achievements
Top Papers
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- 2