Yanbo Pang

Papers

Total Citations

H-Index

About

Yanbo Pang is a robotics researcher whose work focuses on biomimetic control, multi-task coordination, and trajectory tracking for robotic manipulators. His primary research areas include bio-inspired control algorithms, redundant robot control via quadratic programming, and adaptive trajectory tracking in dynamic environments. Pang’s most notable contribution is the CBMC (Cerebellar-Basal Ganglia Model Control) approach, a biomimetic framework for controlling 7-degree-of-freedom robotic arms without requiring prior knowledge of the robot’s dynamic model. This innovation addresses critical challenges in real-world robotics, where model inaccuracies and environmental variations are common. The CBMC paper has garnered 10 citations since 2023, reflecting its growing influence in the field. Additionally, Pang has contributed overviews of multi-task control strategies for redundant robots and methods for trajectory tracking under dynamic conditions. His work bridges neuroscience and robotics, offering practical solutions for adaptive, model-free control that could enhance the autonomy and robustness of robotic systems in manufacturing, healthcare, and service applications.