Multiplicative Extended Kalman Filter for Relative Rotorcraft Navigation

Abstract

In this article we detail the fundamentals of a new approach to GPS-denied navigation for aerial vehicles in confined indoor environments. We depart from the common practice of navigating within a globally referenced map, and instead keep the position and yaw states relative to the current node in the map. The approach combines elements of graph SLAM with a multiplicative extended Kalman filter (MEKF). The filter provides quality state estimates at a fast rate and a graph SLAM algorithm maintains a pose graph. We provide specific details for the relative MEKF. We verify the relative estimation approach with hardware flight test results accompanied by comparisons to motion capture truth. We also provide flight results with estimates in the control loop.

Cushioned extended-periphery avoidance: A reactive obstacle avoidance plugin

“…To emphasize the light-weight nature of CEPA, avoidance was restricted to use less than 1/16 of the available processing time. State estimation was performed using the Relative Multiplicative Extended Kalman Filter described in [18] provided with position measurements from an RGB-D visual odometry algorithm described in [19]. No external positioning system or off-board processing was required.…”

Алгоритм Уточненого Позиціонування В Навігаційних Системах Доповненої Реальності

“…Рекурсивні алгоритми уточнюють значення координат на основі послідовностей зашумлених вимірів у часі, тобто є фільтрами, які на основі зашумлених даних видають статистично оптимальне значення стану системи. Найбільш популярним фільтром в навігаційних системах є фільтр Калмана [6].…”

Multi-sensor robust relative estimation framework for GPS-denied multirotor aircraft

“…This section presents the implementation details of the multi-sensor estimation framework for a multirotor vehicle. The attitude of the vehicle is represented as a quaternion, and the estimator is an indirect multiplicative extended Kalman filter following [11]. The term "multiplicative" refers to the definition of the attitude error as the quaternion multiplication of the true and estimated attitude states:…”