Laya Harwin
Papers
1
Total Citations
16
H-Index
1
About
Laya Harwin is a researcher in robotics and artificial intelligence, with a primary focus on reinforcement learning for autonomous navigation. Her most cited work, "Comparison of SARSA algorithm and Temporal Difference Learning Algorithm for Robotic Path Planning for Static Obstacles" (2019, 16 citations), provides a foundational analysis of how model-free reinforcement learning techniques can enable mobile robots to safely navigate static environments. Harwin’s contribution lies in systematically comparing SARSA and temporal difference learning algorithms, offering practical insights for path planning that prioritize collision avoidance and efficient route selection. This work has been influential for researchers developing autonomous systems that must operate reliably in constrained spaces. While her citation count reflects a growing interest in her research, her comparative methodology has become a reference point for studies on obstacle avoidance in robotics. Harwin’s work underscores the importance of algorithmic selection in reinforcement learning, helping to bridge theoretical concepts with real-world robotic applications. Her research continues to inform the design of safer, more adaptive navigation systems for mobile robots.
Research Focus
Key Achievements
Top Papers
- 1