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Cooperative Visual-Inertial Sensor Fusion: Fundamental Equations

机译:合作视觉惯性传感器融合:基本方程

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This paper provides a new theoretical and basic result in the framework of cooperative visual-inertial sensor fusion. Specifically, the case of two aerial vehicles is investigated. Each vehicle is equipped with inertial sensors (accelerometer and gyroscope) and with a monocular camera. By using the monocular camera, each vehicle can observe the other vehicle. No additional camera observations (e.g., of external point features in the environment) are considered. First, the entire observable state is analytically derived. This state includes the relative position between the two aerial vehicles (which includes the absolute scale), the relative velocity and the three Euler angles that express the rotation between the two vehicle frames. Then, the basic equations that describe this system are analytically obtained. In other words, both the dynamics of the observable state and all the camera observations are expressed only in terms of the components of the observable state and in terms of the inertial measurements. These are the fundamental equations that fully characterize the problem of fusing visual and inertial data in the cooperative case. The last part of the paper describes the use of these equations to achieve the state estimation through an EKF. In particular, a simple manner to limit communication among the vehicles is discussed. Results obtained through simulations show the performance of the proposed solution, and in particular how it is affected by limiting the communication between the two vehicles.
机译:本文提供了合作视觉惯性传感器融合框架的新理论和基本结果。具体地,研究了两个空中车辆的情况。每辆车都配备有惯性传感器(加速度计和陀螺仪)和单眼相机。通过使用单眼相机,每辆车都可以观察到其他车辆。不考虑额外的相机观察(例如,环境中的外部点特征)。首先,整个可观察状态在分析衍生。该状态包括两个空中车辆(包括绝对尺度)之间的相对位置,相对速度和三个欧拉角,其表示两个车辆框架之间的旋转。然后,分析了描述该系统的基本方程。换句话说,可观察状态和所有相机观察的动态均仅在可观察状态的组件和惯性测量方面表达。这些是完全表征合作案例中的融合视觉和惯性数据的问题的基本方程。本文的最后一部分描述了使用这些方程来实现通过EKF的状态估计。特别地,讨论了一种简单的方式来限制车辆之间的通信。通过模拟获得的结果显示了所提出的解决方案的性能,特别是通过限制两个车辆之间的通信的方式如何影响。

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