An agent architecture called ABPEM (Agent-Based Planning, Execution and Monitoring) is presented that utilizes a dynamically reconfigurable data-flow network for planning, execution and monitoring on large-scale multi-information-source systems. This approach is applicable to a broad range of systems, such as transportation, logistics, manufacturing and information-gathering systems, especially where the domain is characterized by dynamic environments that change during the course of execution. It is currently being applied to the problem of validating and verifying airlift cargo schedules. Given an airlift cargo mission schedule, relevant data is identified and collected and then used to (a) validate the future scheduled missions, and (b) verify the completion of executing missions (or reporting unexpected results).

Presents a miniature robotic system ("scout") useful for reconnaissance and surveillance missions. A large number of scout robots are deployed and controlled by humans and/or larger "ranger" robots. The specially designed and constructed scouts are extremely small (roughly 116cc volume) yet are readily deployable (by tossing or launching), have multiple mobility modes, have multiple sensing capabilities, can transmit and receive data and instructions, and have a limited capability for autonomous action. The rangers are significantly larger vehicles, based on a commercial-off-the-shelf platform, augmented with scout launchers, radios, and additional sensors. Together, the scouts and rangers form a hierarchical team capable of carrying out complex missions in a wide variety of environments.

Distributed robotics uses multiple robots through coordination of task to solve problems. Developing a distributed robotic system introduces a number of challenges, one of which is the intra-robot communication and networking of data and commands. Due to the characteristics of the targeted robotic missions and environments, the wireless networking requirements impose stringent constraints in terms of available memory, processing, and power consumption. Designing under these constraints and still providing support for such functions as synchronous commands and proxy processing is the true challenge. This paper discusses research in providing a lightweight wireless routing/networking solution that can dynamically tune the intra-robotic networking to adapt to the robotic team's mission needs and the environment situation encountered.

An approach for a software tool, the Science and Technology Literacy Desktop, that can organize disparate online educational content into coherent lesson plans, automatically generate links to related reference material, and provide assessment of student comprehension is presented. Based on an enhanced Web browser concept it allows access to a wide variety of material and formats, yet provides the controls necessary for an instructor to administer effective lessons. This software takes a significant step beyond current educational software that lack extensibility to a range of information as broad as that found on the Internet.

This research addresses the problem of exchanging modeling information between multiple legacy applications, not initially developed to be interoperable. In this approach, information is shared by multiple applications through utilizing intelligent agent-based common communication protocols and common model and process semantics and structures (i.e. a middleware representation). To assist the conversion of model content to the middleware, a user extendible semantic description (or ontology) of model concepts, entities and relationships is used.

Complex tasks are usually described as high-level goals, leaving out the details on how to achieve them. However, to control a robot, the task must be described in terms of primitive commands for the robot. Having the robot move itself to and through an unknown, and possibly narrow, doorway is an example of such a task. It is shown how the transformation from high-level goals to primitive commands can be performed at execution time and an architecture is proposed based on reconfigurable objects that contain domain knowledge and knowledge about the sensors and actuators available. The approach is illustrated using actual data from a real robot.

Complex robot tasks are usually described as high level goals, with no details on how to achieve them. However, details must be provided to generate primitive commands to control a real robot. A sensor explication concept that makes details explicit from general commands is presented. We show how the transformation from high-level goals to primitive commands can be performed at execution time and we propose an architecture based on reconfigurable objects that contain domain knowledge and knowledge about the sensors and actuators available. Our approach is based on two premises: 1) plan execution is an information gathering process where determining what information is relevant is a great part of the process; and 2) plan execution requires that many details are made explicit. We show how our approach is used in solving the task of moving a robot to and through an unknown, and possibly narrow, doorway; where sonic range data is used to find the doorway, walls, and obstacles. We illustrate the difficulty of such a task using data from a large number of experiments we conducted with a real mobile robot. The laboratory results illustrate how the proper application of knowledge in the integration and utilization of sensors and actuators increases the robustness of plan execution.

Complex tasks are usually described as high-level goals, leaving out the details on how to achieve them. However, to control a robot, details must be provided. Having the robot move itself to and through an unknown, and possibly narrow, doorway is an example of such a task. The authors illustrate the difficulty of such a task using actual data from a real robot. The authors show how the transformation from high-level goals to primitive commands can be performed at execution time and they propose an architecture based on reconfigurable objects that contain domain knowledge and knowledge about the sensors and actuators available. The authors then show how their approach is used in solving the illustrated task.>

Abstract- In order for a mobile robot to accomplish a non-trivial task, the task must be described in terms of primitive actions of the robot’s actuators. Our contention is that the transformation from the high level description of the task to the primitive actions should be performed primarily at execution time, when knowledge about the environment can be obtained through sensors. Our theory is based on the premise that proper application of knowledge increases the robustness of plan execution. We propose to produce the detailed plan of primitive actions and execute it by using primitive components that contain domain specific knowledge and knowledge about the available sensors and actuators. These primitives perform signal and control processing as well as serve as an interface to high-level planning processes. In this work, importance is placed on determining what information is relevant to achieve the goal as well as