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On the design and development of attitude stabilization, vision-based navigation, and aerial gripping for a low-cost quadrotor

机译:关于低成本四旋翼的姿态稳定,基于视觉的导航和空中抓握的设计和开发

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This paper presents the design and development of autonomous attitude stabilization, navigation in unstructured, GPS-denied environments, aggressive landing on inclined surfaces, and aerial gripping using onboard sensors on a low-cost, custom-built quadrotor. The development of a multi-functional micro air vehicle (MAV) that utilizes inexpensive off-the-shelf components presents multiple challenges due to noise and sensor accuracy, and there are control challenges involved with achieving various capabilities beyond navigation. This paper addresses these issues by developing a complete system from the ground up, addressing the attitude stabilization problem using extensive filtering and an attitude estimation filter recently developed in the literature. Navigation in both indoor and outdoor environments is achieved using a visual Simultaneous Localization and Mapping (SLAM) algorithm that relies on an onboard monocular camera. The system utilizes nested controllers for attitude stabilization, vision-based navigation, and guidance, with the navigation controller implemented using a nonlinear controller based on the sigmoid function. The efficacy of the approach is demonstrated by maintaining a stable hover even in the presence of wind gusts and when manually hitting and pulling on the quadrotor. Precision landing on inclined surfaces is demonstrated as an example of an aggressive maneuver, and is performed using only onboard sensing. Aerial gripping is accomplished with the addition of a secondary camera, capable of detecting infrared light sources, which is used to estimate the 3D location of an object, while an under-actuated and passively compliant manipulator is designed for effective gripping under uncertainty.
机译:本文介绍了自主姿态稳定,在非结构化,GPS拒绝的环境中导航,在倾斜表面上主动降落以及在低成本定制四旋翼飞机上使用机载传感器进行空中抓握的设计和开发。利用廉价的现成组件的多功能微型飞行器(MAV)的开发由于噪声和传感器精度而带来了多个挑战,并且实现除导航之外的各种功能还涉及控制挑战。本文通过从头开始开发一个完整的系统来解决这些问题,使用最近在文献中开发的广泛的滤波和姿态估计滤波器来解决姿态稳定问题。使用依赖于车载单眼相机的可视化同时定位和制图(SLAM)算法,可以在室内和室外环境中进行导航。该系统将嵌套控制器用于姿态稳定,基于视觉的导航和制导,导航控制器使用基于S型函数的非线性控制器来实现。该方法的有效性通过即使在阵风的情况下以及手动击中并拉动四旋翼时也能保持稳定的悬停来证明。演示了在倾斜表面上的精确着陆作为激进机动的示例,并且仅使用机载感应进行了精确着陆。空中抓地是通过添加能够检测红外光源的辅助摄像头完成的,该辅助摄像头用于估计物体的3D位置,而欠驱动且被动适应的操纵器设计用于在不确定情况下有效抓地。

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