Robust multi-sensor fusion for micro aerial vehicle navigation in GPS-degraded/denied environments

State estimation for Micro Air Vehicles (MAVs) is challenging because sensing instrumentation carried on-board is severely limited by weight and power constraints. In addition, their use close to and inside structures and vegetation means that GPS signals can be degraded or all together absent. Here we present a navigation system suited for use on MAVs that seamlessly fuses any combination of GPS, visual odometry, inertial measurements, and/or barometric pressure. We focus on robustness against real-world conditions and evaluate performance in challenging field experiments. Results demonstrate that the proposed approach is effective at providing a consistent state estimate even during multiple sensor failures and can be used for mapping, planning, and control.