Chin Kim On
Papers
2
Total Citations
19
H-Index
2
About
Chin Kim On is a researcher whose work sits at the intersection of evolutionary robotics, artificial neural networks, and multi-objective optimization. His primary research focus is on evolving intelligent, minimalist controllers for autonomous robots, enabling them to perform complex collective behaviors without explicit programming. On’s major contributions include pioneering the use of Pareto-based multi-objective evolutionary algorithms to simultaneously optimize both the neural structure and the behavioral performance of robot controllers. His 2010 paper, “Evolution and analysis of self-synthesized minimalist neural controllers for collective robotics using Pareto multi-objective optimization,” with 10 citations, demonstrates how evolved neural networks can successfully coordinate a group of simulated E-puck robots in a collective box-pushing task. Building on this, his 2008 work, “Multi-objective artificial evolution of RF-localization behavior and neural structures in mobile robots” (9 citations), explored both elitist and non-elitist Pareto approaches for evolving RF-localization in Khepera robots. Together, these studies highlight On’s dedication to creating robust, self-organizing robotic systems, offering a scalable path toward more adaptive and autonomous multi-robot teams.
Research Focus
Key Achievements
Top Papers
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