Miin Tyi Chao

Papers

Total Citations

H-Index

About

Miin Tyi Chao is a robotics researcher whose work centres on autonomous navigation and computer vision, with a particular focus on obstacle avoidance for mobile robots. Her most cited paper, “Visually-guided obstacle avoidance” (2003, 19 citations), presents an indoor autonomous system that integrates greyscale camera images processed through Canny edge detection with sonar ranging data. This multi-sensory approach enables robots to perceive and respond to their environment in real time, blending vision and proximity sensing to guide behaviour-based navigation. Chao’s contribution lies in demonstrating how relatively simple visual cues—edge images—can be effectively combined with sonar information to create robust, low-cost obstacle avoidance strategies. While her citation count reflects a focused, early-career impact, her work is notable for its practical, systems-level approach to a core challenge in mobile robotics: enabling machines to move safely through cluttered, dynamic spaces. For students and researchers exploring sensor fusion or behaviour-based control, Chao’s paper offers a clear, implementable example of how vision and range sensors can work together in autonomous systems.