The need for intelligent unmanned vehicles has been steadily increasing. These vehicles could be air-, ground-, space-, or sea-based. This paper will review some of the most common software systems and methods that could be used for controlling such vehicles. Early attempts at mobile robots were confined to simple laboratory environments. For vehicles to operate in realworld noisy and uncertain environments, they need to include numerous sensors and they need to include both reactive and deliberative features. The most effective software systems have been hierarchical or multi-layered. Many of these systems mimic biological systems. This paper reviews several software approaches for autonomous vehicles. While there are similarities, there are differences as well. Most of these software systems are very difficult to use, and few of them have the ability to learn. Autonomous vehicles promise remarkable capabilities for both civilian and military applications, but much work remains to develop intelligent systems software which can be used for a wide range of applications. In particular there is a need for reliable open-source software that can be used on inexpensive autonomous vehicles.

This paper describes an intelligent autonomous airborne flight capability that is being used as a test bed for future technology development. The unmanned air vehicles (UAVs) fly under autonomous control of both an onboard computer and an autopilot. The onboard computer provides the mission control and runs the autonomous Intelligent Controller (IC) software while the autopilot controls the vehicle navigation and flight control. The autonomous airborne flight system is described in detail. An IC architecture directly applicable to the design of unmanned vehicles is also presented. The UAVs may operate independently or in cooperation with one another to carry out a specified mission. The intelligent UAV flight system is used to evaluate and study autonomous UAV control as well as multi-vehicle collaborative control.

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