Noise-Suppressing Newton Algorithm for Kinematic Control of Robots - Xiuchun Xiao; Lin Wei; Dongyang Fu; Jingwen Yan; Huan Wang (IEEE Access)
In this paper, armed with the integral control method, a new noise-suppressing Newton (NSN) algorithm is proposed for the redundancy resolution of redundant robot manipulators efficiently. For practical hardware implementation, the discrete-time noise-suppressing Newton (abbreviated as DTNSN) algorithm is discretized from the continues NSN algorithm. Specifically, the distinguishing feature of the proposed DTNSN algorithm is that it can rigorously converge with inherent tolerance to noises induced by communication jamming and computational systematical errors. In contrast, considerable traditional algorithms often dispose of noises with the high-degree filter from the viewpoint of signal processing, which requires a complex system structure and further results in a heavy computational burden. Note that theoretical analyses are provided to elaborate the convergent property of the DTNSN algorithm polluted with constant bias, time-dependent linear noises and bounded random noises. Besides, by the proposed DTNSN algorithm, the end effector of both serial and parallel redundant robot manipulators complete the allocated motion planning and are impervious to the noisy simulated environment.