Driven by applications like Micro Aerial Vehicles (MAVs), driver-less cars, etc, localization solution has become an active research topic in the past decade. In recent years, Ultra Wideband (UWB) emerged as a promising technology because of its impressive performance in both indoor and outdoor positioning. But algorithms relying only on UWB sensor usually result in high latency and low bandwidth, which is undesirable in some situations such as controlling a MAV. To alleviate this problem, an Extended Kalman Filter (EKF) based algorithm is proposed to fuse the Inertial Measurement Unit (IMU) and UWB, which achieved 80Hz 3D localization with the significantly improved accuracy and almost no delay. To verify the effectiveness and reliability of the proposed approach, a swarm of 6 MAVs is set up to perform a light show in an indoor exhibition hall.
In order to solve the delay and low bandwidth problem caused by the UWB constant speed hypothesis, Li et al. REF proposed an Extended Kalman Filter (EKF)-based algorithm to fuse the inertial measurement unit (IMU) and UWB, in which the state vector of EKF takes into account the acceleration deviation in three directions.
Accurate 3D Localization for MAV Swarms by UWB and IMU Fusion
2018 IEEE 14th International Conference on Control and Automation (ICCA)
2018 IEEE 14th International Conference on Control and Automation (ICCA)
Engineering Computer Science