Modified Newton Integration Algorithm With Noise Tolerance Applied to Robotics

Currently, the Newton-Raphson iterative algorithm has been extensively employed in the fields of basic research and engineering. However, when noise components exist in a system, its performance is largely affected. To remedy shortcomings that the conventional computing methods have encountered in a noisy workspace, a novel modified Newton integration (MNI) algorithm is proposed in this article. In addition, the steady-state error of the proposed MNI algorithm is smaller than that of the Newton-Raphson algorithm under a noise-free or noisy workspace. To lay the foundations for the corresponding theoretical analyses, the proposed MNI algorithm is first converted into a homogeneous linear equation with a residual term. Then, the related theoretical analyses are carried out, which indicate that the MNI algorithm possesses noise-tolerance ability under various noisy environments. Finally, multiple computer simulations and physical experiments on robot control applications are performed to verify the feasibility and advantage of the proposed MNI algorithm.

Automated summary

The article introduces a novel modified Newton integration (MNI) algorithm to address the performance issues caused by noise components in systems, compared to the conventional Newton-Raphson algorithm. The MNI algorithm demonstrates smaller steady-state error and noise-tolerance ability. Theoretical analyses and computer simulations confirm the feasibility and advantages of the proposed MNI algorithm in various noisy environments.