新型刚柔混联连续体机器人运动建模

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关键词：软轴；连续体机器人；运动静力学模型；神经网络；逆运动学中图分类号：TP242DOI：10.3969/j.issn.1004-132X.2025.11.025

Abstract： A study of the kinemetic modeling was carried out for a novel rigid-flexible hybrid continuum robot driven by tension-torsion synergistic actuation. A kinetostatic model was developed based on the piecewise constant curvature（PCC） framework，which comprehensively considered various loads. To solve the highly nonlinear inverse kinematics，a BP neural network model optimized by the NewtonRaphson based optimizer（NRBO），denoted as NRBO-BP model，was constructed. Experimental results show that the average bending angle errors at the end of the single/dual-segment flexible robots are as 4.2∘ and 7.1∘ ， respectively. The maximum position error in trajectory tracking based on NRBO-BP model is as 2.5mm ，which verifies the accuracy and effectiveness of the proposed methods.

Key words： flexible shaft； continuum robot； kinetostatic model; neural network；inverse kinematics

0 引言

近年来，受生物结构启发的连续体机器人凭借其高顺应性与灵巧度为微创手术等场景提供了新技术路径。（剩余9816字）