Jiunhan Chen

Papers

Total Citations

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About

Jiunhan Chen is a robotics researcher whose work bridges evolutionary computation and multi-agent systems, with a primary focus on predator-prey dynamics in robotics. His research centers on developing autonomous robot controllers through evolutionary algorithms, particularly for complex pursuit-evasion scenarios. Chen's major contribution lies in demonstrating the feasibility of evolving behavioral strategies for robot teams in simulation before transferring them to real-world platforms. His most cited work, "Evolutionary predator-prey robot systems" (14 citations), presents a novel approach where robot predators evolve their pursuit strategies over 100 simulated generations followed by 10 generations of real-world optimization. In "Simulated and Real-World Evolution of Predator Robots" (10 citations), he introduced an innovative "smart" prey model using Gaussian danger zones to challenge predator evolution. His framework for learning predator-prey agents from simulation to reality (2020) represents a significant step toward practical deployment of evolved robot controllers. Chen's work has accumulated over 27 citations, establishing him as a contributor to the growing field of evolutionary robotics and sim-to-real transfer learning. His research offers valuable insights for students interested in autonomous systems, evolutionary computation, and multi-robot coordination.