Showing papers on "Autonomous system (mathematics) published in 2002"

A new chaotic attractor coined

Abstract: This letter reports the finding of a new chaotic attractor in a simple three-dimensional autonomous system, which connects the Lorenz attractor and Chen's attractor and represents the transition from one to the other.

A Rigorous ODE Solver and Smale's 14th Problem

Abstract: We present an algorithm for computing rigorous solutions to a large class of ordinary differential equations. The main algorithm is based on a partitioning process and the use of interval arithmetic with directed rounding. As an application, we prove that the Lorenz equations support a strange attractor, as conjectured by Edward Lorenz in 1963. This conjecture was recently listed by Steven Smale as one of several challenging problems for the twenty-first century. We also prove that the attractor is robust, i.e., it persists under small perturbations of the coefficients in the underlying differential equations. Furthermore, the flow of the equations admits a unique SRB measure, whose support coincides with the attractor. The proof is based on a combination of normal form theory and rigorous computations.

Semi-autonomous adaptive cruise control systems

Abstract: The concept of a semi-autonomous adaptive cruise control (SAACC) system is developed, which enjoys significant advantages over present day adaptive cruise control (ACC) systems in terms of highway safety and traffic flow capacity. The semi-autonomous systems combine the deployment advantages of autonomous vehicles with the performance advantages of fully automated highway systems (AHSs) in which vehicles operate cooperatively as a platoon. Unlike platoon systems, the semi-autonomous systems are immediately deployable on present day highways, where both manually driven and adaptive cruise controlled vehicles can coexist. Our theoretical results show that the proposed system is able to maintain smaller time gaps safely, is string stable, and is guaranteed to have smaller actuator inputs than a standard autonomous ACC system. The simulation results indicate that more accurate and smoother tracking, smaller time gaps, smaller control efforts, and increased robustness to vehicle dynamics are achieved by semi-autonomous control.

EMS-Vision: a perceptual system for autonomous vehicles

Abstract: The paper gives a survey on the new Expectation-based Multifocal Saccadic vision (EMS-vision) system for autonomous vehicle guidance developed at the Universitat der Bundeswehr Munchen (UBM). EMS-Vision is the third generation dynamic vision system following the 4-D approach. Its core element is a new camera arrangement, mounted on a high bandwidth pan-tilt head for active gaze control. Central knowledge representation and a hierarchical system architecture allow efficient activation and control of behavioral capabilities for perception and action. The system has been implemented on commercial off-the-shelf (COTS) hardware components in both UBM test vehicles VaMoRs and VaMP Results from autonomous turnoff maneuvers, performed on army proving grounds, are discussed.

Stable periodic motion of a system with state dependent delay

Abstract: We consider an autonomous system of a differential and a functional equation for one-dimensional motion of an object which attempts to regulate its distance from a given point by means of reflected signals. In a suitable, compact state space the forward initial value problem is well-posed. For certain configurations of the parameters involved we prove that there exist periodic orbits which are exponentially stable with asymptotic phase.

Autonomous system topology based auxiliary network for peer-to-peer overlay network

Abstract: A system and method for an auxiliary network for a peer-to-peer overlay network using autonomous system level topology. Using information available through the auxiliary network, expressway connections are established amongst expressway nodes and ordinary connections are established between ordinary and expressway nodes. The connections established is unconstrained and arbitrary. After the connections are established, efficient routing of information may take place.

Dynamical Neural Schmitt Trigger for Robot Control

Abstract: Structure and function of a small but effective neural network controlling the behavior of an autonomous miniatur robot is analyzed. The controller was developed with the help of an evolutionary algorithm, and it uses recurrent connectivity structure allowing non-trivial dynamical effects. The interplay of three different hysteresis elements leading to a skilled behavior of the robot in challenging environments is explicitly discussed.

NASA's Autonomous Formation Flying Technology Demonstration, Earth Observing-1(EO-1)

Abstract: NASA's first autonomous formation flying mission, the New Millennium Program's (NMP) Earth Observing-1 (EO-1) spacecraft, recently completed its principal goal of demonstrating advanced formation control technology. This paper provides an overview of the evolution of an onboard system that was developed originally as a ground mission planning and operations tool. We discuss the Goddard Space Flight Center s formation flying algorithm, the onboard flight design and its implementation, the interface and functionality of the onboard system, and the implementation of a Kalman filter based GPS data smoother. A number of safeguards that allow the incremental phasing in of autonomy and alleviate the potential for mission-impacting anomalies from the on- board autonomous system are discussed. A comparison of the maneuvers planned onboard using the EO-1 autonomous control system to those from the operational ground-based maneuver planning system is presented to quantify our success. The maneuvers discussed encompass reactionary and routine formation maintenance. Definitive orbital data is presented that verifies all formation flying requirements.

Service emergence based on relationship among self-organizing entities

Abstract: In this paper, we describe the Jack-in-the-Net (Ja-Net) architecture for adaptive services in a large scale, open network environment. Using biologically inspired concepts, Ja-Net achieves built-in capabilities to create/emerge services adaptively according to dynamically changing network conditions and user preferences. In Ja-Net, a service is implemented by a collection of autonomous system components called cyber-entities. Cyber-entities are autonomous with simple behaviors and interact with each other using Ja-NetACL (Agent Communication Language) to jointly provide a service. For instance, cyber-entities migrates from node to node and find a new cyber-entity to interact with. Also, cyber-entities may establish a relationship with interaction partners to form a group to provide a service. The strength of the relationship between cyber-entities is a measure for the usefulness of the relationship and is adjusted based on the level of satisfaction indicated by the user who received the service. As relationships grow, cyber-entities self-organize by reducing the number of cyber-entities to interact with based on the strength of the relationship. Consequently, a group of cyberentities emerge to provide services that users prefer. We implemented a prototype of Ja-Net to verify the feasibility of autonomous interaction and service emergence features of Ja-Net.

Trajectory control and its application to approach a target: part i. development of trajectory control algorithms for an autonomous vehicle

Abstract: A control method for autonomous vehicles was developed to steer the vehicle to a given target point. Since four-wheeled vehicles have constraints known as nonholonomic constraints, a nonlinear control theory was applied to generate a trajectory that would permit a vehicle to run from a starting point to its goal within these constraints by tracking it. The method was extended to turns exceeding 90° by deriving a trajectory generation method using polar coordinates. The accuracy of the control was examined by simulation and field experiments. This accurate trajectory-tracing technology can be used to fully automate agricultural operations. Since the proposed control algorithm was an open-loop control, disturbances such as wheel slippage caused navigation error. To minimize error, feedback terms were added by linearizing the vehicle's kinematic equations around a nominal trajectory generated with the open-loop algorithm.

Guiding a mobile robot with cellular neural networks

Abstract: We show how cellular neural networks (CNNs) are capable of providing the necessary signal processing needed for visual navigation of an autonomous mobile robot. In this way, even complex feature detection and object recognition can be obtained in real time by analogue hardware, making fully autonomous real-time operation feasible. An autonomous robot was first simulated and then implemented by simulating the CNN with a DSP. The robot is capable of navigating in a maze following lines painted on the floor. Images are processed entirely by a CNN-based algorithm, and navigation is controlled by a fuzzy-rule-based algorithm. Copyright © 2002 John Wiley & Sons, Ltd.

Utility interactive AC module photovoltaic system with frequency tracking and active power filter capabilities

Abstract: This paper describes an AC module solar PV generation system, a relatively new PV system technology that is intended to be cost-effective and flexible. Based on dispersed and autonomous system control logic, the AC module offers advantages over conventional central-inverter based systems: increased modularity, ease of installation, freedom of system design, and easy system expansion. The system described has frequency tracking capability, enabling two modules at different base frequencies to interoperate stably at a common frequency. Simulation results for various conditions are included, and its operation as an active power filter considered.

Technology for autonomous space systems

Abstract: To meet the demands of operating in distance space environments, there is a need for more autonomous space systems. This document presents a survey of the state-of-the-art in space autonomy. This includes technologies relevant to space system autonomy makes recommendations for future research. These technologies include underlying technologies, component technologies, and space systems. Underlying technologies are general approaches to artificial intelligence. Component technologies are aspects of autonomous system implementation using underlying technologies. The space systems discussed in this survey include all past, current, and near-future missions with significant levels of autonomous behavior as well as a representative, though not exhaustive, discussion of many of the (more typical) directly controlled space systems used. The recommendations for future research in space autonomy consists of a list of five thrust areas requiring further development in order to progress toward higher levels of autonomy for space systems.

A Virtual Reality Tool for Teleoperation Research

Abstract: Efficiency in teleoperation systems is strongly affected by the relationship between the operator and the remote environment If the operator has access to easily comprehensible information, his capability for opportune decision making increases Virtual reality has been shown to be an effective means of displaying information to the human operator It allows the creation of three-dimensional and interactive environments, which can be explored and controlled in an intuitive way. In our system, called ASSET, we have applied virtual reality techniques in the design and implementation of a teleoperation system's human-machine interface. ASSET's objective was to create an object-oriented software framework for teleoperation systems development This tool allows flexible customizing and can be used as a test bed for evaluating interaction techniques, devices, simulation models and for research about autonomous agents.

Relating Autonomy to a Task - Can It Be Done?

Abstract: : There are currently countless methods touting being the best at autonomous control. whether it is emergent behavior or dynamic programming, fuzzy logic or Bayesian Belief Networks, each technology has its phalanx of zealots that proclaim it to be superior for the job and the rest rotten, or at least trivialized. In this paper, we step back and look at the big picture in autonomous control, developing the idea that what will drive the choice of the particular technology is the task, or tasks, that the autonomous system must do, and not the merits of any particular technology by itself. The optimal technology for any task in inexorably intertwined with the task - they cannot be separated.

A new simulation framework for autonomy in robotic missions

Abstract: Autonomy is a key enabling factor in the advancement of robotics for remote exploration. As the level of resources devoted to this effort continues to increase, it has become equally important to provide simulation tools and environments to scientists in which to test the autonomy algorithms. While industrial robotics benefits from a variety of high quality simulation tools, researchers developing autonomy software are still dependent primarily on block-world simulations. The Mission Simulation Facility (MSF) project addresses this shortcoming by providing a simulation toolkit that will enable developers of autonomous control systems to test their Systems' performance against integrated, standardized simulations of NASA mission scenarios. The MSF provides a distributed architecture that connects the autonomous system to a set of simulated components replacing the robot hardware and its environment.

System and method for identifying addresses to modify and the effects thereof

Abstract: A system and method identifies ranges of addresses that can be reallocated and/or split to cause traffic to be redirected in a network to reduce the utilization of the most utilized links in an autonomous system. The system and method then identifies the utilization of the autonomous system after the reallocation and/or split and reports on the differences of utilization pre- and post-split.

Intelligent behavior generator for autonomous mobile robots using planning-based AI decision making and supervisory control logic

Abstract: In earlier research the Center for Self-Organizing and Intelligent Systems (CSOIS) at Utah State University (USU) have been funded by the US Army Tank-Automotive and Armaments Command's (TACOM) Intelligent Mobility Program to develop and demonstrate enhanced mobility concepts for unmanned ground vehicles (UGVs). One among the several out growths of this work has been the development of a grammar-based approach to intelligent behavior generation for commanding autonomous robotic vehicles. In this paper we describe the use of this grammar for enabling autonomous behaviors. A supervisory task controller (STC) sequences high-level action commands (taken from the grammar) to be executed by the robot. It takes as input a set of goals and a partial (static) map of the environment and produces, from the grammar, a flexible script (or sequence) of the high-level commands that are to be executed by the robot. The sequence is derived by a planning function that uses a graph-based heuristic search (A* -algorithm). Each action command has specific exit conditions that are evaluated by the STC following each task completion or interruption (in the case of disturbances or new operator requests). Depending on the system's state at task completion or interruption (including updated environmental and robot sensor information), the STC invokes a reactive response. This can include sequencing the pending tasks or initiating a re-planning event, if necessary. Though applicable to a wide variety of autonomous robots, an application of this approach is demonstrated via simulations of ODIS, an omni-directional inspection system developed for security applications.

Real-Time Forecasting by Bio-Inspired Models

Abstract: In recent years, bio-inspired methods for problem solving, such as Arti cial Neural Networks (ANNs) or Genetic and Evolutionary Algorithms (GEAs), have gained an increasing acceptance as alternative approaches for forecasting, due to advantages such as nonlinear learning and adaptive search. The present work reports the use of these techniques for Real-Time Forecasting (RTF), where there is a need for an autonomous system capable of fast replies. Comparisons among bioinspired and conventional approaches (e.g., Exponential Smoothing), revealed better forecasting performances for the evolutionary and connectionist models.

Multiple Autonomous Robots for UXO Clearance, the Basic UXO Gathering System (Bugs) Project

Abstract: The Naval Explosive Ordnance Disposal Technology Division (NAVEODTECHDIV) has had an active program for several years for the development of technologies required to realize an autonomous system of small robots to clear areas of unexploded submunition. The focus, thus far, has been on the technology elements themselves, with an emphasis on the multiple robot operation approach and autonomous cooperative-behavior control system and processing. NAVEODTECHDIV is in full-scale testing of the system operation and performance.

Self-organizing systems with self-diagnosability

Abstract: Constructing a system capable of functioning without any human support over an extended period is the aim of many engineers. However it is generally considered to be difficult to make decentralized self-organizing autonomous system fault-tolerant. In this paper, we propose to apply the theory of highly structured self-diagnosable systems to this problem. As an example, we apply the theory and recursive procedures method of fault-tolerant system construction to a decentralized self-organizing autonomous robotic system that forms a circle. The result of simulation shows the usefulness of the proposed method. The highly structured self-diagnosable system has an O(|E|)fault-identification algorithm that can diagnose each of the units in the system independently, locally and in any order, where E and |E| mean the set of the directed edges and its cardinality, respectively.

Target location by self-organizing autonomous air vehicles

Abstract: Target location is a problem where the application of multiple sensors that are geographically distributed can determine or improve the location estimate of a target. If these sensors are capable of cooperative behaviour then the information from each sensor can be autonomously fused to provide an estimate of the target position. The individual sensors may be quite unsophisticated, yet the observation system that is created through cooperation and adaptive networking of these sensors provides sufficient process gain to achieve target location accuracies similar to those of expensive centralized sensor systems. The accuracy of target location estimates depends heavily on the separation distance between the sensors. Large baseline geometry takes advantage of many seemingly unsophisticated bearing measurements that are organised into a coordinated observation system to locate a target. Team formation is one method to address coordination of distributed sensors, data fusion, sensor resource and energy management, and communication link control based on the concept of cooperating machines1,2,3. We apply an algorithm for agent team formation4 inspired by the self-organising behaviour observed in colonies of ants, to the problem of integrating the sensors of a group of networked mini-Autonomous Air Vehicles (AAVs). The mini-AAVs are tasked to locate targets within a region of interest. The challenge we address is to make the location estimation system adaptive to a dynamic environment and robust to failure. Simulation results are presented which address issues in distributed data fusion, sensor resource and energy management, and communication link control, for a group of mini-AAVs.© (2002) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Path planning is no substitute for intelligent behavior

Abstract: This paper describes our experience implementing navigation behavior for two different autonomous multi-robot systems using two very different approaches. We describe the problems encountered and their solutions and the extensions necessary to support planning for multiple robots in our application domains. We conclude that there are many applications of path-planning that would be well served by the introduction of a little domain specific intelligent behavior as a substitute for brute force path planning over unnecessarily large configuration spaces.