Sapam Jitu Singh

Papers

Total Citations

279

H-Index

About

Sapam Jitu Singh is a leading researcher in robotics and artificial intelligence, with a primary focus on intelligent motion planning and autonomous navigation. His most significant contribution is a groundbreaking deterministic improved Q-learning algorithm for mobile robot path planning, which revolutionized traditional reinforcement learning approaches. By introducing a presumed knowledge of distance metrics between states, Singh developed a method that updates Q-table entries in a single pass using four derived properties, dramatically improving computational efficiency. This seminal work, published in 2013, has garnered over 270 citations, establishing it as a cornerstone reference in the field of robot path planning. Singh has also advanced the state of the art in dynamic environment navigation through his Fuzzy-GA method combined with a Three Path concept, which enables robots to effectively handle both static and dynamic obstacles. His research bridges the gap between theoretical machine learning and practical robotics applications, offering efficient solutions for real-world autonomous systems. Singh’s work continues to influence researchers and engineers developing intelligent navigation systems for mobile robots in complex environments.