Wee Kheng Leow
Papers
10
Total Citations
207
H-Index
6
About
Wee Kheng Leow is a robotics and artificial intelligence researcher whose work has made significant contributions to autonomous mobile robotics, multi-robot systems, and neural network-based motion control. His research spans several interconnected areas, including hybrid robot architectures, self-organizing neural networks, and distributed multi-robot cooperation — fields that sit at the intersection of planning, perception, and intelligent control. Among his most influential contributions is his development of hybrid mobile robot architectures that tightly integrate deliberative planning with reactive control, work that has garnered over 60 citations and challenged the traditional divide between these two paradigms. He further advanced this line of inquiry by applying Cooperative Extended Kohonen Maps (EKMs) to complex robot motion tasks, demonstrating how ensemble neural approaches can elegantly handle real-time sensorimotor challenges. His autonomic mobile sensor network framework, cited 68 times, introduced a dynamic coalition-based task allocation scheme enabling resource-constrained robots to cooperate effectively across coverage regions. Early work on smell-guided exploration also reflects his breadth of curiosity beyond conventional sensing modalities. Across his career, Leow has consistently pushed toward more adaptive, self-organizing robotic systems, leaving a meaningful mark on the foundations of autonomous multi-robot coordination.
Research Focus
Key Achievements
Top Papers
- 1
- 2A hybrid mobile robot architecture with integrated planning and control63 citations · 2002
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- 6Computational Studies of Exploration by Smell6 citations · 1998
- 7A hybrid mobile robot architecture with integrated planning and control4 citations · 2002
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