Imitation-Based Motion Planning and Control of a Multi-Section Continuum Robot Interacting With the Environment
Imitation-Based Motion Planning and Control of a Multi-Section Continuum Robot Interacting With the Environment
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DOI：
10.1109/lra.2023.3239306
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发表时间：
2023-03
影响因子：
5.2
通讯作者：
Ibrahim A. Seleem;Haitham El-Hussieny;H. Ishii
中科院分区：
文献类型：
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作者：
Ibrahim A. Seleem;Haitham El-Hussieny;H. Ishii
近年来，柔性机器人由于其在机动性和安全性方面优于刚性机器人而变得越来越重要，这使得它们能够在非结构化环境中工作，例如在医疗应用中。然而，柔性机械臂的运动规划和控制是具有挑战性的，由于其顺应性行为和系统的不确定性。因此，这封信提出了一种基于模仿的运动规划（IbMP）的方法，沿着与动态阻抗控制的学习，规划，和轨迹跟踪的两部分软连续体机器人在动态环境中。点对点的运动演示，包括机器人的尖端位置和方向直观地提供了一个运动捕捉系统（OptiTrack V120-trio）和一个类似的运动灵活的接口。此外，基于拉格朗日公式和泰勒展开级数的两节连续体机器人的奇异性自由的动力学模型，推导出同时规划机器人运动。仿真结果表明，IbMP方法，沿着的动态阻抗控制，通过改变机器人的尖端位姿的初始和目标，同时避免静态和动态障碍物，并移动回期望的轨道后，干扰，推广机器人的运动。最后，IBMP算法对输入干扰的稳定性和性能进行评估，使用蒙特卡罗方法，可以指导增益值的选择。
Recently, flexible robots are growing in importance owing to their merits over rigid robots in maneuverability and safety, which equips them to work in unstructured environments, such as occur in medical applications. However, motion planning and control of flexible manipulators is challenging due to their compliance behavior and system uncertainties. Thus, this letter presents an Imitation-based Motion Planning (IbMP) approach, along with dynamic impedance control for learning, planning, and trajectory tracking of a two-section soft continuum robot in a dynamic environment. Point-to-point motion demonstrations, including the robot's tip position and orientation are intuitively provided by a motion capture system (OptiTrack V120-trio) and a similar kinematic flexible interface. Additionally, a singularity-free dynamic model based on Lagrangian formulation and Taylor expansion series of a two-section continuum robot is derived while planning for robot motions. The simulation results show that the IbMP approach, along with the dynamic impedance control, generalizes the robot's motion by varying the initial and goal of the robot's tip pose while avoiding static and dynamic obstacles, and moving back to the desired track after disturbances. Finally, the stability and performance of the IbMP algorithm against input disturbances are assessed using a Monte Carlo approach that can guide the selection of gain values.