Online task planning and control for fuel-constrained aerial robots in wind fields

Real-world applications of aerial robots must consider operational constraints such as fuel level during task planning. This paper presents an algorithm for automatically synthesising a continuous non-linear flight controller given a complex temporal logic task specification that can include contingency planning rules. Our method is a hybrid controller where fuel level is treated continuously in the low-level and symbolically in the high-level. The low-level controller assumes the availability of a set of point-estimates of wind velocity and builds a continuous interpolation using Gaussian process regression. Fuel burn and aircraft dynamics are modelled under physically realistic assumptions. Our algorithm is efficient and we show empirically that it is feasible for online execution and replanning. We present several extended simulation examples of navigation in a wind field and surveillance with fuel constraints, including two different implementations of the low-level controller and also an example where the wind field varies over time.