Online task planning and control for aerial robots with fuel constraints in winds

Abstract

Real-world applications of aerial robots must consider operational constraints such as fuel level during task planning. This paper presents an algorithm for automatically synthesizing 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 showempirically that it is feasible for online execution and replanning. We present simulation examples of navigation in a wind field and surveillance with fuel constraints.