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 the development of a system that uses computational psychology (the Soar cognitive architecture) for the control of unmanned vehicles. A multithreaded software system written using Java and integrated with the Soar cognitive architecture has been implemented on two types of mobile robots. Soar can be used as a general purpose robotic intelligence system and can handle a wide variety of sensor inputs and motor-control outputs. The use of existing computational psychology methods (such as Soar) may be a more efficient approach to developing robotic software, rather than developing new software for every new unmanned vehicle application. Results from the application of this software system (named the cognitive robotic system, or CRS) to a practical unmanned ground vehicle mission, navigating to a target GPS location while avoiding obstacles, are described. The CRS has been designed so that its capabilities can be expanded in the future through the inclusion of additional sensors and motors, additional software systems, and more sophisticated Soar agents.

Abstract-This paper discusses the use of the Soar cognitive architecture to control gait selection of a sixlegged robot using force sensors attached to its feet. The hardware platform also incorporated sonar sensors, a GPS receiver, and a webcam. The Soar cognitive architecture was used to control the robot, and the Java programming language was used as middleware between Soar and the hardware components. The force sensors were attached and the force profile was examined. Soar productions for controlling the gait were developed. Experiments were performed on terrain which has random holes and obstacles. Two cases were conducted: walking using Soar to select the gait, and using Soar with the chunking turned on for learning.

This paper describes the development of the Cognitive Robotic System (CRS) for studying intelligent and autonomous unmanned vehicles. This system uses a multi-threaded software system written using Java to integrate the Soar cognitive architecture with a sixlegged mobile robot and its sensors and motors. The results of experiments in which the Cognitive Robotic System was used to control the hexapod on missions of GPS navigation with obstacle avoidance are described. The CRS was designed so that its capabilities can be expanded in the future through the inclusion of additional software systems and more sophisticated Soar agents.

This paper describes a new introductory level course in software engineering for aerospace engineering students. It offers the fundamental concepts of software engineering to senior-level and graduate aerospace engineering students through lectures and a team project. The material in the lectures support the timeline of the team project. The class project differs from projects of other software engineering courses because each student works in a small group representing one process in a software development model, and each group is part of a large team. The instructor acted as a customer who indicated system needs. The project goal was to develop a small software system for a teleoperated mobile robot. The team project reinforced the concepts from the class and tried to demonstrate how software engineering works in a simulated industrial environment. The feedback from students in the class was evaluated through a survey and a focus group discussion (presented in a separate paper). Courses such as these are essential since software and computing can be 50% of the cost of modern aircraft and spacecraft. In order to make aerospace engineering degrees as useful as possible, modern curriculum must include material beyond the traditional aerodynamics, structures, propulsion, and dynamics/control areas.