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Mobile robot control on uneven and slippery ground: An adaptive approach based on a multi-model observer

机译:凹凸不平地面上的移动机器人控制:基于多模型观测器的自适应方法

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This paper proposes an algorithm dedicated to off-road mobile robot path tracking at high speed. In order to ensure a high accuracy, a predictive and adaptive approach is developed to face the various perturbations due to this context (mainly the bad grip conditions and the terrain geometry). The control law is based on previous work, and requires the knowledge of sideslip angles, which cannot be directly measured. As a result, an observer based on two levels of modeling (kinematic and dynamic) is proposed to ensure a relevant and fast estimation. If the kinematic part is independent from the terrain geometry, the dynamic model used in this paper requires to take explicitly into account the influence of the terrain geometry on mobile robot dynamic. It is achieved by the introduction of the lateral robot inclination, which is on-line estimated via a Kalman filter and integrated into the dynamical model. The advantages of the proposed contribution to path tracking control are investigated through full-scale experiments achieved at high speed (up to 6m/s) on an uneven and grass field.
机译:本文提出了一种专用于越野移动机器人高速路径跟踪的算法。为了确保高精度,开发了一种预测性和自适应方法来应对由于这种情况而引起的各种干扰(主要是不良的抓地力条件和地形几何形状)。控制律以先前的工作为基础,需要了解无法直接测量的侧滑角知识。结果,提出了基于两个建模水平(运动学和动态学)的观察者以确保相关且快速的估计。如果运动学部分独立于地形几何形状,则本文中使用的动力学模型需要明确考虑地形几何形状对移动机器人动力学的影响。这是通过引入横向机器人倾斜度来实现的,该倾斜度是通过卡尔曼滤波器进行在线估算并集成到动力学模型中的。通过在不平坦的草地上高速(最高6m / s)进行的全面实验,研究了拟议的路径跟踪控制贡献的优势。

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