Integration of Self-Awareness in Multi-vehicle Autonomous Control

Abstract

One enabler for true unmanned, autonomous vehicle operation is mission awareness composed of three components: knowledge of mission objectives, internal self-situational awareness, and external self-situational awareness. Internal self-situational awareness implies knowledge of platform health and capability. External self-situational awareness encompasses knowledge of external resources (supplies, supervisors, or collaborators) as well as threats that can affect system performance. Finally, the system must be able to translate mission objectives into actions and assess the impact of its internal and external state on its ability to execute the mission. If the combination of the internal and external state will not permit the system to achieve its mission objectives, then the autonomous control system for the platform must revise the mission plan. In the case of multi-vehicle autonomous control, an autonomous supervisor may be required to alter the mission plan for one or more platforms. This paper describes the use of a behavior-based, intelligent control architecture to integrate both internal-self situational awareness, external self-situational awareness, and autonomous control. The scalability of the architecture simplifies the addition of a hierarchical supervisor that can communicate with other collaborators to revise mission plans in the event of changes in the internal or external situation.