Tonghan Lan
Papers
1
Total Citations
7
H-Index
1
About
Tonghan Lan is a researcher in robotics and computational kinematics, with a focus on applying neural network methods to solve complex inverse kinematics problems. His most cited work, "Neural Network Based Inverse Kinematics Solution for 6-R Robot Implement Using R Package Neuralnet" (2021, 7 citations), introduces a novel approach to calculating the inverse kinematics of the ABB IRB7600-500, a 6-revolute joint robot arm. Lan's contribution addresses a critical limitation of traditional methods, which often fail to achieve the precision required for industrial tasks. By leveraging the R package neuralnet, he demonstrates how neural networks can minimize positional error during robot arm movement from one point to another in the workspace. This work highlights the potential of machine learning to enhance robotic accuracy and efficiency, offering a practical alternative for real-world applications. Lan's research bridges the gap between theoretical kinematics and industrial robotics, making him a notable figure in the field. His findings are particularly valuable for students and researchers exploring neural network-based solutions in robotics, showcasing how computational tools can overcome longstanding challenges in motion planning and control.
Research Focus
Key Achievements
Top Papers
- 1