Max Robotics — Global Service Robot Directory + US Certification

About

Ming-Yuan Shieh is a pioneering roboticist whose research bridges intelligent service robotics, human-robot interaction, and autonomous navigation. His most influential work, "Design of an intelligent hospital service robot and its applications" (24 citations), established foundational frameworks for deploying robots in healthcare settings, integrating navigation path planning with information decision-making systems to reduce human resource burdens. Shieh has made significant contributions to real-time computer vision, notably through his PCA and SVM-PSO based face recognition system (22 citations), which dramatically improved dynamic image recognition validity. His research extends to biped locomotion control, where he developed adaptive neuro-fuzzy inference system (ANFIS) controllers and artificial neural network-based gait balancing systems, advancing the stability and autonomy of humanoid robots. Shieh also pioneered vision-based shopping assistant robots and interactive nurse robots, demonstrating practical applications of service robotics in commercial and home environments. His work on gesture recognition for human-robot interactive control and GA-PSO optimized fuzzy controllers for robot soccer showcases his expertise in merging evolutionary algorithms with real-time robotic control. Through these innovations, Shieh has established himself as a key figure in developing intelligent, socially-aware robots capable of navigating complex human environments.