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About

Chin Kuan Ho is a researcher whose work lies at the intersection of swarm robotics and evolutionary computation, with a particular focus on enhancing Particle Swarm Optimization (PSO) for real-world applications. His primary contributions center on the development and refinement of the Area Extension PSO (AEPSO) algorithm, a modified PSO designed to overcome the limitations of basic PSO in static, dynamic, noisy, and real-time environments. Ho’s most influential work, “Applying Area Extension PSO in Robotic Swarm” (33 citations), demonstrates how AEPSO can effectively coordinate robotic swarms, while his second most-cited paper, “Navigating a robotic swarm in an uncharted 2D landscape” (32 citations), explores autonomous exploration and navigation in unknown terrains. He has also investigated the effects of communication range, noise, and help-request signals on AEPSO performance, as well as cooperative learning strategies for both homogeneous and heterogeneous particle swarms. Collectively, Ho’s research has garnered over 77 citations, establishing him as a notable contributor to swarm intelligence and multi-robot systems, with his AEPSO framework offering a robust alternative to traditional evolutionary algorithms like genetic algorithms.