基于 Koopman 的机器人柔性针三维路径跟踪控制

Nianhua Zhang, Zhi Qi, Jicheng Chen, Hui Zhang, Hamid Reza Karimi
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摘要

机器人柔性针头能够在复杂的解剖结构中穿梭,并高精度地到达目标,因此在微创医疗手术中备受关注。为了解决三维环境中的复杂控制问题,本文提出了一种基于 Koopman 数据驱动的控制策略。首先,使用具有穿刺运动学的简化高维自行车模型来模拟三维(3D)路径跟踪问题。然后,利用 Koopman 算子理论,设计并训练有限线性近似,以简化柔性针的非线性系统。最后,在线性近似的基础上,提出了一种基于 Koopman 的模型预测控制(MPC)方案,以实现柔性针的三维路径跟踪。基于仿真,线性近似和数据驱动控制策略得到了验证。
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Koopman‐based 3‐dimensional path following control for robotic flexible needles
Robotic flexible needles have gained significant attention in minimally invasive medical procedures due to their ability to navigate complex anatomical structures and reach targets with high precision. Addressing the complex control problem in a 3‐dimensional environment, a Koopman‐based data‐driven control strategy is proposed in this paper. First, a 3‐dimensional (3D) path tracking problem is modeled using the simplified high‐dimensional bicycle model with the puncture kinematic. Then, with the Koopman operator theory, a finite linear approximation is designed and trained to simplify the nonlinear system of flexible needles. Finally, based on the linear approximation, a Koopman‐based model predictive control (MPC) scheme is proposed to realize 3‐dimensional path tracking for flexible needles. Based on simulations, the linear approximation and data‐driven control strategy are validated.
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