Worker safety is ofparamount importance in industries where harsh working environments are the norm. The research being conducted by this group aims to take workers out ofharm's way by creating an automated control system for fleets of intelligent machines that will do the dirty work, while the humans oversee the system to ensure proper operation. The focus of the research is not on machine intelligence, but rather on the system that will control the fleet in unstructured or semistructured locales. Mine environments are used as a target for this research, which is broken into a few main sections. The first section deals with dynamically creating task schedules for the vehicles based on possibly changing environmental conditions. The second section deals with resource sharing between multiple vehicles, especially the sharing ofroadways to ensure operational safety. This is done using Petri net data structures and theory. Thirdly, since the machines may not be able to independently cope with obstacles they encounter, human intervention capability is required. Fourthly, for human operators to make sense of the system's overall state and requests, development of a human-machine interface is necessary. Experiments have been conducted which demonstrate the successful use ofthis framework to control two model-size intelligent machines given one shared resource, namely a two-road intersection. In the future the group intends on imposing greater loads on the system (i.e. more vehicles and shared resources), and on integrating more complex human intervention capabilities, finer vehicle control, and improved system state monitoring.