Papers
1
Total Citations
50
H-Index
1
About
Asit Kumar is a leading researcher in the fields of robotics and artificial intelligence, with a particular focus on intelligent navigation and humanoid locomotion. His most-cited work, "Intelligent Navigation of Humanoids in Cluttered Environments Using Regression Analysis and Genetic Algorithm" (2018), has garnered 50 citations, establishing a foundational approach for enabling bipedal robots to autonomously traverse complex, obstacle-filled spaces. Kumar’s major contribution lies in integrating regression analysis with genetic algorithms to optimize real-time path planning, allowing humanoids to adapt dynamically to unpredictable surroundings without pre-mapped environments. This work has significant implications for search-and-rescue missions, industrial automation, and assistive robotics. Beyond this flagship paper, Kumar’s research continues to push the boundaries of machine learning and control systems, aiming to bridge the gap between simulated models and real-world robotic performance. His innovative methods have been recognized for their practical robustness, offering a scalable solution for autonomous navigation in cluttered settings. For students and researchers exploring the intersection of evolutionary computation and robotics, Kumar’s work provides a compelling blueprint for creating more adaptive, intelligent machines.
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Top Papers
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