Papers
2
Total Citations
68
H-Index
2
About
Ehsan Samiei is a robotics researcher whose work lies at the intersection of control theory, optimization, and autonomous navigation. His primary research areas include the control of underactuated robotic systems on Lie groups, particularly SE(3), and the development of novel path planning algorithms for mobile robots operating in dynamic environments. His most influential contribution, "Integrated Guidance and Feedback Control of Underactuated Robotics System in SE(3)" (2017, 40 citations), presents a unified framework for simultaneously guiding and stabilizing underactuated vehicles—a significant advance for aerial and underwater robots that cannot be fully actuated. Samiei also introduced the Random Particle Optimization Algorithm (RPOA) in his 2013 paper (28 citations), a bio-inspired method drawing from bacterial foraging techniques to enable real-time local path planning in unknown, changing environments. This work offers a computationally efficient alternative to traditional planners, allowing robots to navigate around obstacles without prior maps. With over 68 citations across his top papers, Samiei’s contributions are particularly valuable for researchers working on autonomous vehicles, nonlinear control, and motion planning in unstructured settings.
Research Focus
Key Achievements
Top Papers
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- 2