  We propose a fixed-lag smoother-based sensor fusion architecture to leverage
the complementary benefits of range-based sensors and visual-inertial odometry
(VIO) for localization. We use two fixed-lag smoothers (FLS) to decouple
accurate state estimation and high-rate pose generation for closed-loop
control. The first FLS combines ultrawideband (UWB)-based range measurements
and VIO to estimate the robot trajectory and any systematic biases that affect
the range measurements in cluttered environments. The second FLS estimates
smooth corrections to VIO to generate pose estimates at a high rate for online
control. The proposed method is lightweight and can run on a computationally
constrained micro-aerial vehicle (MAV). We validate our approach through
closed-loop flight tests involving dynamic trajectories in multiple real-world
cluttered indoor environments. Our method achieves
decimeter-to-sub-decimeter-level positioning accuracy using off-the-shelf
sensors and decimeter-level tracking accuracy with minimally-tuned open-source
controllers.
