Maryam Shoaran
Papers
6
Total Citations
51
H-Index
4
About
Maryam Shoaran is a robotics researcher whose work bridges the gap between bio-inspired control systems and practical hardware implementation. Her research spans three key areas: locomotion control for bipedal robots, computer vision for robotic manipulation, and hardware-software co-design for autonomous systems. Her most impactful work, a comprehensive survey on hardware implementation of SLAM algorithms (23 citations), provides crucial guidance for deploying simultaneous localization and mapping on resource-constrained platforms. Shoaran has made notable contributions to bipedal locomotion through bio-inspired Central Pattern Generator approaches for gait generation and transition, as well as fuzzy control systems for variable-speed running. In computer vision, she developed GSPnP, a geometric solution to the Perspective-n-Point problem, and algorithms for ball trajectory estimation using single-camera systems. Her recent work includes a modified convergence DDPG algorithm for robotic manipulation, demonstrating her growing expertise in deep reinforcement learning. Shoaran’s research is particularly valuable for students and engineers working on real-world robotic systems, as she consistently addresses the practical challenges of implementing complex algorithms on physical hardware.
Research Focus
Key Achievements
Top Papers
- 1
- 2A Modified Convergence DDPG Algorithm for Robotic Manipulation9 citations · 2023
- 3GSPnP: simple and geometric solution for PnP problem8 citations · 2019
- 4
- 5Fuzzy control of bipedal running with variable speed and apex height4 citations · 2019
- 6