Lina Cheng

Papers

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About

Lina Cheng is a robotics researcher whose work focuses on bio-inspired autonomous navigation for mobile robots operating in unknown environments. Her most-cited paper, "Autonomous navigation research for mobile robot" (2012), introduces a novel navigation scheme that simulates the operant conditioning mechanism—a learning process from behavioral psychology. By designing a "tendency cell" based on information entropy, Cheng's approach allows robots to adaptively navigate without pre-mapped environments, representing a significant contribution to intelligent robotics and autonomous systems. Though her citation count is modest, her work bridges cognitive science and robotics, offering foundational insights for adaptive navigation algorithms. Cheng's research is particularly relevant for applications in search-and-rescue, exploration, and autonomous vehicles, where real-time decision-making in dynamic settings is critical. Her innovative use of bionic strategies continues to inspire further studies in robot learning and environmental interaction.