Johnny Koh Siaw Paw
Papers
2
Total Citations
15
H-Index
2
About
Driven by a passion for intelligent robotics, Johnny Koh Siaw Paw has made significant contributions to the fields of computational intelligence and autonomous navigation. His research primarily focuses on optimizing robotic systems through advanced algorithms, with a key emphasis on solving complex kinematic problems and path planning. In his highly regarded 2012 work, "Comparison between genetic algorithm and electromagnetism-like algorithm for solving inverse kinematics" (8 citations), Koh pioneered a novel comparison of the Electromagnetism-Like Algorithm against Genetic Algorithms for solving the inverse kinematics of a four-link planar robot manipulator, providing critical insights into algorithmic accuracy and efficiency. This work is foundational for researchers seeking to enhance robotic precision. Earlier, in 2009, he introduced a groundbreaking approach in "Cognitive Map approach for mobility path optimization using multiple objectives genetic algorithm" (7 citations), where he synergized Cognitive Map methods with genetic algorithms to derive streamlined, collision-free paths for mobile robots in static environments. This innovative work demonstrates his ability to merge cognitive science with evolutionary computation, offering a robust framework for autonomous navigation. Koh’s research continues to inspire advancements in intelligent robotics and optimization.
Research Focus
Key Achievements
Top Papers
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