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A FLAT MODEL PREDICTIVE CONTROLLER FOR TRAJECTORY TRACKING IN IMAGE BASED VISUAL SERVOING

机译:基于图像视觉伺服的轨迹跟踪平面模型预测控制器

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摘要

Image-Based Visual Servoing (IBVS) is a control strategy using visual information to control the motion of robotic systems. Classical IBVS can not take into account either the mechanical constraints (joint and actuator limitations) or the visibility constraints, very important in this scheme. Model Predictive Control (MPC) is well adapted to deal with these drawbacks. However, applied to fast systems (e.g. mobile robots), the computational time is a great challenge for real time applications. One way to reduce this time is to use the concept of differential flatness. In this paper, a new IBVS strategy based on a flat MPC approach is proposed. The capabilities of this approach in terms of trajectory tracking and obstacle avoidance are pointed out. Applied to mobile robot trajectory tracking, a simulation experiment shows the efficiency and the robustness of this new control scheme. The computational time required by the proposed solution is compared with the nonlinear solution and easily enables a real-time application.
机译:基于图像的Visual Serving(IBV)是使用可视信息来控制机器人系统的运动的控制策略。古典IBV无法考虑机械约束(关节和执行器限制)或可见性约束,在该方案中非常重要。模型预测控制(MPC)很适应处理这些缺点。然而,应用于快速系统(例如移动机器人),计算时间是实时应用的巨大挑战。减少此时间的一种方法是使用差分平整度的概念。本文提出了一种基于扁平MPC方法的新IBVS策略。指出了这种方法在轨迹跟踪和避免避免方面的能力。应用于移动机器人轨迹跟踪,仿真实验显示了这种新控制方案的效率和鲁棒性。将所提出的解决方案所需的计算时间与非线性解决方案进行比较,并且易于启用实时应用。

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