Papers
12
Total Citations
117
H-Index
6
About
Mohammadreza Davoodi is a robotics and control systems researcher whose work spans multi-agent systems, precision agriculture automation, and safe human-robot interaction. His research is distinguished by its breadth — bridging rigorous mathematical control theory with real-world robotic applications. Davoodi has made significant contributions to autonomous multi-robot deployment and coverage control, developing graph-theoretic and energy-aware strategies for distributing heterogeneous robot teams across agricultural environments with no human intervention, work that has attracted nearly 50 citations across related publications. His distributed deployment frameworks address practical challenges such as nonlinear robot dynamics, partially known environments, and heterogeneous team compositions. Beyond agricultural robotics, Davoodi has pioneered integration of probabilistic movement primitives with control barrier functions, enabling robots to learn complex manipulation tasks from human demonstrations while providing formal safety guarantees — a critical advancement for collaborative human-robot workspaces. His adaptive neural network backstepping controller for flexible joint manipulators, already accumulating 17 citations since 2023, further demonstrates his versatility across control design challenges. With research touching swarm formation control, model predictive safety frameworks, and even biomechanical modeling of elderly balance, Davoodi represents a researcher committed to translating sophisticated control theory into systems that meaningfully interact with and assist people.
Research Focus
Key Achievements
Top Papers
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- 2Coverage Control with Multiple Ground Robots for Precision Agriculture23 citations · 2018
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- 9Probabilistic Movement Primitive Control via Control Barrier Functions4 citations · 2021
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