Ultra-Wideband-Based Localization for Quadcopter Navigation

Abstract

Micro unmanned aerial vehicles (UAVs) are promising to play more and more important roles in both civilian and military activities. Currently, the navigation of UAVs is critically dependent on the localization service provided by the Global Positioning System (GPS), which suffers from the multipath effect and blockage of line-of-sight, and fails to work in an indoor, forest or urban environment. In this paper, we establish a localization system for quadcopters based on ultra-wideband (UWB) range measurements. To achieve the localization, a UWB module is installed on the quadcopter to actively send ranging requests to some fixed UWB modules at known positions (anchors). Once a distance is obtained, it is calibrated first and then goes through outlier detection before being fed to a localization algorithm. The localization algorithm is initialized by trilateration and sustained by the extended Kalman filter (EKF). The position and velocity estimates produced by the algorithm will be further fed to the control loop to aid the navigation of the quadcopter. Various flight tests in different environments have been conducted to validate the performance of UWB ranging and localization algorithm.

Graph Optimization Approach to Range-Based Localization

“…For the comparison with existing methods (UKF, EKF, nonlinear regression (NR), MDS, RVFL) [11], [17], [22], [23], we implemented their algorithms in the same environment of our lab with the best choices of parameters to ensure the fairness of the comparison. The results of moving horizon estimation and particle filter method are from [32], [36], [41].…”

“…From the experimental results in the existing range-based localization methods [11], [17], [22], [23], we find that their performance in the altitude direction is generally not as good as other directions. Some possible solutions include: (i) Adding altitude sensors such as Laser beam or Lidar to measure the altitude, but it requires the ground to be even; (ii) Placing anchors on the ceiling, but it may also be difficult for many environments.…”

On-board communication-based relative localization for collision avoidance in Micro Air Vehicle teams

“…This has enabled formation flying (Min et al 2016) and large-scale flocking (Vásárhelyi et al 2014). In indoor tasks, where GNSS is not available, absolute position data can be measured using external sensors/beacons in a known configuration, such as: motion tracking cameras (Michael et al 2010), fixed wireless transmitters/receivers (Guo et al 2016;Ledergerber et al 2015), or visual markers (Faigl et al 2013). However, these solutions are unsuitable for exploration tasks of unknown and unstructured environments.…”

Robust Target-Relative Localization with Ultra-Wideband Ranging and Communication

“…Notice that equations (2), (3), (4) are used for prediction while (5) is for the correction stage. Moreover, the gyroscope biases in the IMU measurements are also accounted for by introducing extra states beside the ten main states in (1). We will update the state estimateX of X using the discretized and linearized versions of the differential equations (2), (3), (4).…”