Chen Bo

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About

Chen Bo is a robotics researcher whose work bridges the gap between humanoid locomotion and intelligent robotic manipulation. His early contributions include the design of a 23-degree-of-freedom small humanoid robot integrated with ZMP force sensors, a foundational project that has garnered 6 citations and advanced the understanding of balance control in bipedal systems. More recently, Bo has focused on the critical challenge of RGB-D-based robotic grasping, proposing ADFNet—a two-branch network enhanced by an attention mechanism that effectively fuses complementary heterogeneous data from color and depth images while maintaining real-time performance. This work, cited 3 times, addresses a key limitation of single-modality approaches and one-branch architectures, offering a more robust solution for autonomous grasping. By tackling both the mechanical design of humanoid platforms and the perceptual intelligence needed for dexterous manipulation, Chen Bo demonstrates a versatile research portfolio that contributes to the evolution of robots capable of interacting with the physical world in dynamic, unstructured environments.