Artificial Intelligence and Systems Theory: Applied to Cooperative Robots

This paper describes an approach to the design of a population of cooperative robots based on concepts borrowed from Systems Theory and Artificial Intelligence. The research has been developed under the SocRob project, carried out by the Intelligent Systems Laboratory at the Institute for Systems and Robotics - Instituto Superior Tecnico (ISR/IST) in Lisbon. The acronym of the project stands both for "Society of Robots" and "Soccer Robots", the case study where we are testing our population of robots. Designing soccer robots is a very challenging problem, where the robots must act not only to shoot a ball towards the goal, but also to detect and avoid static (walls, stopped robots) and dynamic (moving robots) obstacles. Furthermore, they must cooperate to defeat an opposing team. Our past and current research in soccer robotics includes cooperative sensor fusion for world modeling, object recognition and tracking, robot navigation, multi-robot distributed task planning and coordination, including cooperative reinforcement learning in cooperative and adversarial environments, and behavior-based architectures for real time task execution of cooperating robot teams

Cooperative analysis expert situation assessment research

For the past few decades, Rome Air Development Center (RADC) has been conducting research in Artificial Intelligence (AI). When the recent advances in hardware technology made many AI techniques practical, the Intelligence and Reconnaissance Directorate of RADC initiated an applications program entitled Knowledge Based Intelligence Systems (KBIS). The goal of the program is the development of a generic Intelligent Analyst System, an open machine with the framework for intelligence analysis, natural language processing, and man-machine interface techniques, needing only the specific problem domain knowledge to be operationally useful. The development of KBIS is described

Expert system decision support for low-cost launch vehicle operations

Progress in assessing the feasibility, benefits, and risks associated with AI expert systems applied to low cost expendable launch vehicle systems is described. Part one identified potential application areas in vehicle operations and on-board functions, assessed measures of cost benefit, and identified key technologies to aid in the implementation of decision support systems in this environment. Part two of the program began the development of prototypes to demonstrate real-time vehicle checkout with controller and diagnostic/analysis intelligent systems and to gather true measures of cost savings vs. conventional software, verification and validation requirements, and maintainability improvement. The main objective of the expert advanced development projects was to provide a robust intelligent system for control/analysis that must be performed within a specified real-time window in order to meet the demands of the given application. The efforts to develop the two prototypes are described. Prime emphasis was on a controller expert system to show real-time performance in a cryogenic propellant loading application and safety validation implementation of this system experimentally, using commercial-off-the-shelf software tools and object oriented programming techniques. This smart ground support equipment prototype is based in C with imbedded expert system rules written in the CLIPS protocol. The relational database, ORACLE, provides non-real-time data support. The second demonstration develops the vehicle/ground intelligent automation concept, from phase one, to show cooperation between multiple expert systems. This automated test conductor (ATC) prototype utilizes a knowledge-bus approach for intelligent information processing by use of virtual sensors and blackboards to solve complex problems. It incorporates distributed processing of real-time data and object-oriented techniques for command, configuration control, and auto-code generation

Students’ Evolving Meaning About Tangent Line with the Mediation of a Dynamic Geometry Environment and an Instructional Example Space

In this paper I report a lengthy episode from a teaching experiment in which fifteen Year 12 Greek students negotiated their definitions of tangent line to a function graph. The experiment was designed for the purpose of introducing students to the notion of derivative and to the general case of tangent to a function graph. Its design was based on previous research results on students’ perspectives on tangency, especially in their transition from Geometry to Analysis. In this experiment an instructional example space of functions was used in an electronic environment utilising Dynamic Geometry software with Function Grapher tools. Following the Vygotskian approach according to which students’ knowledge develops in specific social and cultural contexts, students’ construction of the meaning of tangent line was observed in the classroom throughout the experiment. The analysis of the classroom data collected during the experiment focused on the evolution of students’ personal meanings about tangent line of function graph in relation to: the electronic environment; the pre-prepared as well as spontaneous examples; students’ engagement in classroom discussion; and, the role of researcher as a teacher. The analysis indicated that the evolution of students’ meanings towards a more sophisticated understanding of tangency was not linear. Also it was interrelated with the evolution of the meaning they had about the inscriptions in the electronic environment; the instructional example space; the classroom discussion; and, the role of the teacher

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 323)

This bibliography lists 125 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during April, 1989. Subject coverage includes; aerospace medicine and psychology, life support systems and controlled environments, safety equipment exobiology and extraterrestrial life, and flight crew behavior and performance

Real-Time GPS-Alternative Navigation Using Commodity Hardware

Modern navigation systems can use the Global Positioning System (GPS) to accurately determine position with precision in some cases bordering on millimeters. Unfortunately, GPS technology is susceptible to jamming, interception, and unavailability indoors or underground. There are several navigation techniques that can be used to navigate during times of GPS unavailability, but there are very few that result in GPS-level precision. One method of achieving high precision navigation without GPS is to fuse data obtained from multiple sensors. This thesis explores the fusion of imaging and inertial sensors and implements them in a real-time system that mimics human navigation. In addition, programmable graphics processing unit technology is leveraged to perform stream-based image processing using a computer\u27s video card. The resulting system can perform complex mathematical computations in a fraction of the time those same operations would take on a CPU-based platform. The resulting system is an adaptable, portable, inexpensive and self-contained software and hardware platform, which paves the way for advances in autonomous navigation, mobile cartography, and artificial intelligence

Large structural impact localization based on multi-agent system

In practical applications of structural health monitoring, a huge amount of distributed sensors are usually used to monitor structures of large dimensions. In order to obtain fast and accurate evaluation of a structure, a multi-agent system is introduced to manage different sensor sets and to fuse distributed information. In this paper, a multi-agent system based on impact location is presented to deal with the impact load localization problem for large-scale structures. The monitoring system firstly detects whether an impact event happens in the monitored subregion, and focuses on the impact source on the sub-region boundary to obtain the sensor network data with blackboard systems. Then the collaborative evaluation of both the acoustic emission and the inverse analysis localization method is employed to obtain precise and fast localization result. Finally, a reliable assessment for the whole structure is provided by fusing evaluation results from the sub-regions. The performance of the proposed multi-agent system is illustrated by means of experimental on a large aerospace aluminum plate structure. Extensive testing of the proposed system demonstrated its effectiveness for the impact load localization in each sub-region, particularly for impacts lying next to the borders of the sub-regions

Image and interpretation using artificial intelligence to read ancient Roman texts

The ink and stylus tablets discovered at the Roman Fort of Vindolanda are a unique resource for scholars of ancient history. However, the stylus tablets have proved particularly difficult to read. This paper describes a system that assists expert papyrologists in the interpretation of the Vindolanda writing tablets. A model-based approach is taken that relies on models of the written form of characters, and statistical modelling of language, to produce plausible interpretations of the documents. Fusion of the contributions from the language, character, and image feature models is achieved by utilizing the GRAVA agent architecture that uses Minimum Description Length as the basis for information fusion across semantic levels. A system is developed that reads in image data and outputs plausible interpretations of the Vindolanda tablets

The Use of the Blackboard Archiecture for a Decision making System for the Control of Craft with various Actuator and Movement Capabilities

This paper provides an overview of an approach to the control of multiple craft with heterogeneous movement and actuation characteristics that is based on the Blackboard software architecture. An overview of the Blackboard architecture is provided. Then, the operational and mission requirements that dictate the need for autonomous control are characterized and the utility of the Blackboard architecture is for meeting these requirements is discussed. The performance of a best-path solver and naïve solver are compared. The results demonstrate that the best-path solver outperforms the naïve solver in the amount of time taken to generate a solution, however, the number of solver-runs to be executed against the Blackboard must be sufficient to allow the lower individual-run times to offset the time required to propagate the data utilized by the best-path solver for solution generation through the database. The existence of other justifications for this approach (even if the number of runs for each data propagation cycle is not sufficient) is also discussed