Autonomous vehicles rely on path planning to guide them towards their destination. These paths are susceptible to interruption by impassable hazards detected at the local scale via on-board sensors, and malicious disruption. We define robustness as an additional parameter which can be incorporated into multi-objective optimization functions for path planning. The robustness at any point is the output of a function of the isochrone map at that point for a set travel time. The function calculates the sum of the difference in area between the isochrone map and the isochrone map with an impassable semi-circle hazard inserted in each of the four cardinal directions. We calculate and compare two different Pareto paths which use robustness as an input parameter with different weights.