E.W. Andarge
Papers
1
Total Citations
2
H-Index
1
About
E.W. Andarge is an emerging researcher at the forefront of autonomous systems and intelligent robotics, with a primary focus on mobile robot navigation and reinforcement learning. Their most cited work, "Mobile Robot Navigation System Using Reinforcement Learning with Path Planning Algorithm" (2024), addresses a critical bottleneck in autonomous vehicle deployment: the complexity and sensor demands of traditional simultaneous localization and mapping (SLAM) methods. By integrating reinforcement learning with path planning algorithms, Andarge proposes a more adaptive and computationally efficient navigation framework that reduces reliance on expensive sensor arrays. This contribution is particularly timely as the field shifts toward learning-based approaches for real-world autonomy. Though early in their career, with the paper garnering 2 citations, Andarge’s work signals a promising trajectory in bridging classical control limitations with modern AI-driven solutions. Their research holds potential for advancing cost-effective, robust navigation in dynamic environments—a key step toward practical autonomous vehicles.
Research Focus
Key Achievements
Top Papers
- 1