Steven Y. Goldsmith

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.

Collective Search by Mobile Robots using Alpha-Beta Coordination

One important application of mobile robots is searching a geographical region to locate the origin of a specific sensible phenomenon. Mapping mine fields, extraterrestrial and undersea exploration, the location of chemical and biological weapons, and the location of explosive devices are just a few potential applications. Teams of “robotic bloodhounds” have a simple common goal; to converge on the location of the source phenomenon, confirm its intensity, and to remain aggregated around it until directed to take some other action. In cases where human intervention through teleoperation is not possible, the robot team must be deployed in a territory without supervision, requiring an autonomous decentralized coordination strategy. This paper presents the alpha-beta coordination strategy, a family of collective search algorithms that are based on dynamic partitioning of the robotic team into two complementary social roles according to a sensor-based status measure. Robots in the alpha role are risk-takers, motivated to improve their status by exploring new regions of the search space. Robots in the beta role are motivated to improve but are conservative, and tend to remain aggregated and stationary until the alpha robots have identified better regions of the search space. Roles are determined dynamically by each member of the team based on the status of the individual robot relative to the current state of the collective. Partitioning the robot team into alpha and beta roles results in a balance between exploration and exploitation, and can yield collective energy savings and improved resistance to sensor noise and defectors. Alpha robots waste energy exploring new territory, and are more sensitive to the effects of ambient noise and to defectors reporting inflated status. Hypothetically, beta robots conserve energy by moving in a direct path to regions of confirmed high status. Beta robots also resist the effects of noise and defectors by averaging status data, but must rely on alpha robots to improve their performance. Alpha-beta is a reactive strategy that requires directed communication of instantaneous sensor data among team members, but does not rely on a domain model. Alpha-beta coordination is a new and ongoing research effort. We present the basic concepts behind the alpha-beta strategy and exhibit preliminary simulation data that illustrate the collective search modes in an idealized search domain.

Decentralized Control for a Swarm of Vehicles Performing Source Localization

In this paper, decentralized feedback controls are presented for a swarm of autonomous, robotic vehicles that is tasked with localizing a stationary, time-invariant source. The development of the feedback controls is motivated by classic function-minimization theory and the method is actually suited for a large collection of agents, where collection of agents may refer to, for example, a population of N design points in some variable space. We present the theory that supports the method, some example problems and their simulations to illustrate the method, and discuss some potential applications.

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.

Analysis of Decentralized Variable Structure Control for Collective Search by Mobile Robots

This paper presents an analysis of a decentralized coordination strategy for organizing and controlling a team of mobile robots performing collective search. The alpha- beta coordination strategy is a family of collective search algorithms that allow teams of communicating robots to implicitly coordinate their search activities through a division of labor based on self-selected roles. In an alpha- beta team, alpha agents are motivated to improve their status by exploring new regions of the search space. Beta agents are conservative, and rely on the alpha agents to provide advanced information on favorable regions of the search space. An agent selects its current role dynamically based on its current status value relative to the current status values of the other team members. Status is determined by some function of the agents sensor readings, and is generally a measurement of source intensity at the agents current location. Variations on the decision rules determining alpha and beta behavior produce different versions of the algorithm that lead to different global properties. The alpha-beta strategy is based on a simple finite-state machine that implements a form of Variable Structure Control (VSC). The VSC system changes the dynamics of the collective system by abruptly switching at defined states to alternative control laws. In VSC, Lyapunovs direct method is often used to design control surfaces which guide the system to a given goal. We introduce the alpha- beta algorithm and present an analysis of the equilibrium point and the global stability of the alpha-beta algorithm based on Lyapunovs method.

Software Requirements Specification for Information Management for Grid Control

This Software Requirements Specification defines the functions of a simulation power grid model. The model defines grid control functions that focus on real-time control and related communication of information among entities that share the operation of the power grid. Deregulation of the power markets necessitates increased communications among entities who have economic motivation to restrict access to important information from other market participants. New power market concepts will impact how planning and real-time control are performed. The simulation power grid model provides the tool for investigating issues of distributed computing, data sharing, data access, communication system capacity, and communications reliability. The model enables researchers to develop intelligent distributed control agents for managing Area Control Error and transmission security. The software requirements specification is defined using a subset of the Unified Modeling Language, a class diagram describing all of the objects along with their attributes, methods, and some modified use cases. The work described in this report was coordinated by the Consortium for Electric Reliability Technology Solutions on behalf of the Assistant Secretary of Energy Efficiency and Renewable Energy, Offce of Power Technologies of the U S . Department ofEnergy under Contract No. DE-ACO4-94AL85000.

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.

Agent-Based Mediation and Cooperative Information Systems

This report describes the results of research and development in the area of communication among disparate species of software agents. The two primary elements of the work are the formation of ontologies for use by software agents and the means by which software agents are instructed to carry out complex tasks that require interaction with other agents. This work was grounded in the areas of commercial transport and cybersecurity.