Dibash Adhikari
Papers
1
Total Citations
39
H-Index
1
About
Dibash Adhikari is a researcher advancing the field of robotic manipulation and autonomous navigation, with a primary focus on intelligent path planning and control systems. His most cited work, "A Novel Hybrid Path Planning Method Based on Q-Learning and Neural Network for Robot Arm" (2021, 39 citations), introduces a groundbreaking approach that synergizes reinforcement learning with neural networks to overcome the limitations of traditional algorithms like RRT and APF. This hybrid method significantly reduces computational costs and planning time while enabling robot arms to navigate complex environments with dynamic obstacles—a critical contribution to manufacturing automation. Adhikari’s research addresses persistent challenges in robotics, such as slow convergence and high energy consumption, by integrating adaptive learning mechanisms. His work has been widely recognized for its practical applicability in industrial settings, earning citations from peers developing real-time robotic systems. Beyond path planning, Adhikari explores sensor fusion and machine learning for autonomous agents, positioning him as a key figure in bridging theoretical AI with tangible robotic solutions. His contributions continue to inspire new generations of engineers seeking efficient, scalable automation technologies.
Research Focus
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Top Papers
- 1