Bin Jin

PLA Rocket Force University of Engineering, Shanghai University, Drexel University

Papers

Total Citations

H-Index

About

Bin Jin has made pioneering contributions to the fields of humanoid robotics and intelligent manipulator control, with a career focused on bridging simulation and real-world robotic performance. His most influential work, "A Simulation Platform Design of Humanoid Robot Based on SimMechanics and VRML" (2011, 18 citations), introduced a groundbreaking virtual environment that enables researchers to develop and test humanoid robot algorithms without requiring physical hardware—a critical tool for labs with limited resources. Earlier, Jin tackled the fundamental challenge of robotic manipulator dynamics in "Robotic manipulator trajectory control using neural networks" (2005, 5 citations), proposing neural network-based control schemes to handle complex, nonlinear systems. His foundational research in "The trajectory planning and tracking of redundant manipulators by a hierarchical neurocontroller" (2002, 2 citations) demonstrated an innovative dual-ANN architecture, combining a Hopfield network for inverse kinematics with a hierarchical controller for motion planning. Across these works, Jin has consistently advanced the integration of artificial neural networks into robotics, enabling more adaptive, precise, and hardware-independent solutions. His simulation platform remains a valuable resource for students and researchers entering humanoid robotics, while his neural control methods continue to inform modern approaches to manipulator trajectory tracking.