Shannon V. Spires

Exhaustive Geographic Search with Mobile Robots Along Space-Filling Curves

Swarms of mobile robots can be tasked with searching a geographic region for targets of interest, such as buried land mines. The authors assume that the individual robots are equipped with sensors tuned to the targets of interest, that these sensors have limited range, and that the robots can communicate with one another to enable cooperation. How can a swarm of cooperating sensate robots efficiently search a given geographic region for targets in the absence of a priori information about the target`s locations? Many of the obvious approaches are inefficient or lack robustness. One efficient approach is to have the robots traverse a space-filling curve. For many geographic search applications, this method is energy-frugal, highly robust, and provides guaranteed coverage in a finite time that decreases as the reciprocal of the number of robots sharing the search task. Furthermore, it minimizes the amount of robot-to-robot communication needed for the robots to organize their movements. This report presents some preliminary results from applying the Hilbert space-filling curve to geographic search by mobile robots.

A Multi-agent System for Coordinating International Shipping

Moving commercial cargo across the US-Mexico border is currently a complex, paper-based, error-prone process that incurs expensive inspections and delays at several ports of entry in the Southwestern US. Improved information handling will dramatically reduce border dwell time, variation in delivery time, and inventories, and will give better control of the shipment process. The Border Trade Facilitation System (BTFS) is an agent-based collaborative work environment that assists geographically distributed commercial and government users with transshipment of goods across the US-Mexico border. Software agents mediate the creation, validation and secure sharing of shipment information and regulatory documentation over the Internet, using the World-Wide Web to interface with human actors. Agents are organized into Agencies. Each agency represents a commercial or government agency. Agents perform four specific functions on behalf of their user organizations: (I) agents with domain knowledge elicit commercial and regulatory information from human specialists through forms presented via web browsers; (2) agents mediate information from forms with diverse ontologies, copying invariant data from one form to another thereby eliminating the need for duplicate data entry; (3) cohorts of distributed agents coordinate the work flow among the various information providers and they monitor overall progress of the documentation and the location of the shipment to ensure that all regulatory requirements are met prior to arrival at the border; (4) agents provide status information to human actors and attempt to influence them when problems are predicted.

Autonomous agents and multi –agent systems (AAMAS) for the military – issues and challenges

The military domain is a very challenging environment and human endeavour in this domain is characterized by uncertainty and the need to be able to deal with significant and disruptive dynamic changes. In addition, activities are driven by human decision-makers who need support in making sense of the environment and with reasoning about, and effecting, possible futures. Hence, various unique factors need to be taken into account when considering the provision of applications, tools, devices and infrastructure for the military domain. This paper will itemize and discuss some of these factors in the context of autonomous agents and multi-agent systems. This paper is a desiderata for the research space.

An intelligent electrical outlet for autonomous load control for electric power grids with a large percentage of renewable resources

We describe an experimental intelligent electrical outlet that is capable of autonomously controlling loads in a smart grid or micro-grid environment without a centralized computer. The outlet comprises four receptacles, each with voltage sensing, current sensing, actuation, a CPU for implementing closed loop control, and an Ethernet bridge for communicating with other outlets and for transmitting data to a collection PC. The outlet can measure the direction of power flow, and the real and reactive components to power. We demonstrate multiple outlets adapting the collective load to the available supply from one and two photovoltaic inverter sources, responding to changes in ~ 100ms intervals.

Knowledge Discovery and Data Mining (KDDM) survey report.

The large number of government and industry activities supporting the Unit of Action (UA), with attendant documents, reports and briefings, can overwhelm decision-makers with an overabundance of information that hampers the ability to make quick decisions often resulting in a form of gridlock. In particular, the large and rapidly increasing amounts of data and data formats stored on UA Advanced Collaborative Environment (ACE) servers has led to the realization that it has become impractical and even impossible to perform manual analysis leading to timely decisions. UA Program Management (PM UA) has recognized the need to implement a Decision Support System (DSS) on UA ACE. The objective of this document is to research the commercial Knowledge Discovery and Data Mining (KDDM) market and publish the results in a survey. Furthermore, a ranking mechanism based on UA ACE-specific criteria has been developed and applied to a representative set of commercially available KDDM solutions. In addition, an overview of four R&D areas identified as critical to the implementation of DSS on ACE is provided. Finally, a comprehensive database containing detailed information on surveyed KDDM tools has been developed and is available upon customer request.