Sara Mashhouri
Papers
1
Total Citations
3
H-Index
1
About
Sara Mashhouri is a robotics researcher specializing in intelligent control systems, autonomous navigation, and computer vision for mobile robots. Her work focuses on integrating reinforcement learning with real-time perception to enable adaptive, obstacle-aware robot behavior. In her most-cited paper, "Reinforcement Learning based Sequential Controller for Mobile Robots with Obstacle Avoidance" (2022), she developed a novel framework combining YOLO-v4 object detection with depth sensing in ROS to create a sequential controller that dynamically avoids obstacles while planning paths. This contribution bridges deep learning and classical control, offering a practical solution for real-world robotic autonomy. Though early in her career, her research has already garnered attention for its innovative fusion of vision-based detection and reinforcement learning, laying groundwork for more resilient mobile robot systems. Her work is particularly relevant for applications in warehouse automation, search-and-rescue, and service robotics, where safe, real-time navigation is critical. As she continues to publish, Mashhouri’s contributions promise to advance the frontier of intelligent, perception-driven robot control.
Research Focus
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Top Papers
- 1