Samiullah Khan
Papers
1
Total Citations
8
H-Index
1
About
Dr. Samiullah Khan is a leading researcher at the intersection of robotics, autonomous navigation, and deep reinforcement learning. His work focuses on developing robust control algorithms that enable self-driving systems and robotic platforms to operate with high precision in complex, dynamic environments. In his most cited work, Khan introduced a novel approach combining deep reinforcement learning with Simultaneous Localization and Mapping (SLAM) to optimize self-driving path tracking. Specifically, he proposed a Reward Shaping Deep Deterministic Policy Gradient (RS-DDPG) algorithm, which addresses critical challenges of low accuracy and poor robustness in robotic control during maneuvers. This contribution has already garnered 8 citations since its 2025 publication, signaling its immediate impact on the field. Khan’s research is pivotal for advancing autonomous systems, bridging the gap between theoretical reinforcement learning and practical robotic applications. His work is essential reading for students and engineers seeking to understand how intelligent control policies can be trained to navigate uncertain, real-world terrains.
Research Focus
Key Achievements
Top Papers
- 1