Showing papers on "Autonomous system (mathematics) published in 2001"

An Experimental Comparative Study of Autonomous and Co-operative Vehicle-follower Control Systems

Abstract: This paper is a comparative study of the performance of constant-time-gap autonomous control systems and co-operative longitudinal control systems that use inter-vehicle communication. Analytical results show that the minimum time gap that can be achieved in autonomous control is limited by the bandwidth of the internal dynamics of the vehicle. Experimental results from typical sensors and actuators are used to show that in practice it is very difficult to achieve a time gap less than 1 s with autonomous vehicle following. This translates to an inter-vehicle spacing of 30 m at highway speeds and a theoretical maximum traffic flow of about 3000 vehicles per hour. The quality of radar range and range rate measurements pose limitations on the spacing accuracy and ride quality that can be achieved in autonomous control. Dramatic improvements in the trade-off between ride quality and spacing accuracy can be obtained merely by replacing radar range rate in the autonomous control algorithm with the difference between the measured velocities of the two cars (a rudimentary form of co-operation). As a baseline comparison, the experimental performance of fully co-operative control is presented. An inter-vehicle spacing of 6.5 m is maintained in a platoon of 8 co-operative vehicles with an excellent ride quality and an accuracy of ±20 cm. Extending this to a 10-vehicle platoon makes it possible to achieve theoretical maximum traffic flows of about 6400 vehicles per hour. Another issue of importance addressed in the paper is the need to accommodate malfunctions in radar (ranging sensor) measurements. Measurement errors can occur due to hardware malfunctions as well as due to road curves, grades and the highway environment in the case of large inter-vehicle spacing. The ability of a co-operative control system to monitor the health of the radar and correct for such errors and malfunctions is demonstrated experimentally.

Expectation-Oriented Analysis and Design

Abstract: A key challenge for agent-oriented software engineering is to develop and implement open systems composed of interacting autonomous agents. On the one hand, there is a need for permitting autonomy in order to support desirable system properties such as decentralised control. On the other hand, there is a need for restricting autonomy in order to reduce undesirable system properties such as unpredictability. This paper introduces a novel analysis and design method for open agent-oriented software systems that aims at coming up to both of these two contrary aspects. The characteristics of this method, called EXPAND, are as follows: (i) it allows agents a maximum degree of autonomy and restricts autonomous behaviour only if necessary (ii) it uses system-level expectations as a key modelling abstraction and as the primary level of analysis and design; and (iii) it is sociologically grounded in Luhmann's systems theory. The application of EXPAND is illustrated in a "car-trading platform" case study.

A two-level, protocol-based approach to controlling autonomous oceanographic sampling networks

Abstract: Autonomous oceanographic sampling networks (AOSNs) are groups of autonomous underwater vehicles and other instrument platforms. They were envisioned to address the serious undersampling problem that exists for the ocean. Advanced AOSNs will include numerous heterogeneous components and perform complex, long-duration missions. They will have to cope with vehicles failing, new vehicles arriving, and changes in the mission and environment. Controlling such a system is a very challenging task. The Cooperative Distributed AOSN control (CoDA) project focuses on developing intelligent control mechanisms for advanced AOSNs. CoDA treats AOSN components as agents that follow protocols to create an effective organization to carry out the mission. CoDA is a two-level approach. A meta-level organization (MLO) first self-organizes from a subset of the agents to discover the AOSNs' total capability repertoire, then designs a task-level organization (TLO) to efficiently carry out the mission. When changes occur, the MLO can step in to reorganize the AOSN to fit the changed situation. This two-level approach allows the AOSN to be both efficient and flexible in the face of change. In addition to describing CoDA, this paper also presents simulation results to show its behavior, both normally and when agents fail.

Initial value problems for systems of ordinary first and second order differential equations with a singularity of the first kind

Abstract: Abs t r ac t : Analytical properties like existence, uniqueness and smoothness of bounded solutions of nonlinear singular initial value problems for ordinary differential equations of first and second Order are considered. Particular attention is paid to the structure of initial conditions which are necessary and sufficient for the Solution to be continuous. A M S 1991 subject Classification: 34A12

A high-fidelity ocean sampling mobile network (SAMON) simulator testbed for evaluating intelligent control of unmanned underwater vehicles

Abstract: The Ocean Sampling Mobile Network (SAMON) simulator testbed has been developed at Penn State for designing and evaluating multirobot ocean-mapping missions, in realistic underwater environments, prior to in-water testing. The goal in developing the testbed is to enable web-based integration of high-fidelity simulators of heterogeneous autonomous undersea vehicles from multiple organizations and a variety of on-board and fixed sensors in a realistic ocean environment in order to formulate and evaluate intelligent control strategies for mission execution. A formal control language facilitates real-time interactions between heterogeneous autonomous components. A simulation experiment is described that demonstrates multistage inferencing and decision/control strategies for spatio-temporal coordination and multilayered adaptation of group behavior in response to evolving environmental physics or operational dynamics.

Autonomous agents for traffic simulation and control

Abstract: The development of an infrastructure for multiple autonomous agents, with an application to urban traffic signal control, is described. The agent-based infrastructure, Cybele, allows for distributed computing, interagent communication, agent migration, and computational resource allocation. The agents that are used to solve the traffic signal control problem are known collectively as DAARTS (Decentralized Adaptive Agents for contRol of Traffic Signals). DAARTS adopts a hierarchical multiagent-based architecture in which the lowest level (intersection agents) involves individual intersection-traffic dynamics and phase selection based on "local" information, while higher levels take into account the supervisory (network-level) dynamics. The controller design is based on a receding-horizon model predictive control approach. Coordination between inter-sections is achieved in a decentralized manner at the lowest level. The agents are integrated into a simulation test bed with the microsimulator CORSIM, using t...

A Semi-Autonomous Reactive Control Architecture

Abstract: This paper presents a novel intelligent control architecture for semi-autonomous systems. A semi-autonomous system is defined here as that autonomous system (machine) which interacts intelligently with a human user (collaborator) who might command, modify, or override its behavior. This work has been motivated by the need for a control architecture that can interact with human users of different perceptual and cognitive capabilities. A dynamic arbitration layer forms the core of the proposed architecture. Accordingly, the architecture evolves around three main variables: degree of autonomy to reflect the user's capabilities, user's level of confidence in commanding the machine, and strength of conflict between the user's command and the machine's autonomous command. The analogy between this architecture and horseback riding is presented and finally a demonstrative application example of a robotic wheelchair is given.

Precision Hybrid Inertial/Acoustic Navigation System for a Long‐Range Autonomous Underwater Vehicle

Abstract: The Canadian Department of National Defence has developed an autonomous underwater vehicle (AUV) capable of performing long-range missions in ice-covered waters. Autonomous operations in such an extreme environment, where a priori knowledge of the bathymetry is frequently limited, requires a navigation system that is precise, reliable, and repeatable. A hybrid navigation system has been developed that provides precise navigation by combining data from two different types of sensors—inertial and acoustic. This navigation system has been integrated into a large AUV, and for mission lengths of up to 200 km has demonstrated horizontal navigational accuracies of better than 0.05 percent of distance traveled. This paper describes the AUV and its mission, the specific navigation sensors selected, and how the overall navigation solution is mechanized. It also describes the behavior of the navigation system during field experiments and during a successful long-range under-ice mission in the High Arctic.

Structuring of Large-scale Complex Hybrid Systems: from Illustrative Analysis toward Modelization

Abstract: System structuring is paramount to the development of large-scale complex hybrid systems (LCHS). However, there is no well-established and effective methodology for the structuring of LCHS. Using the approach of illustrating and abstracting, this paper investigates the structuring of LCHS based on a wide variety of applications. First, intrinsic attributes of LCHS are explored. Then, a unified framework-based analysis is made of six typical examples of LCHS, i.e. human brain-body systems, autonomous robot systems, autonomous fed-batch reactor systems, human-car driving systems, autonomous urban traffic systems, and autonomous production (manufacturing/industrial process) systems. In this way, common characteristics among typical examples, e.g., perception–decision link, distributing, nesting, hierarchy, multiple gradation and hybrid dynamics over a spectrum of time drivers, and, incidentally, wide application orientations of LCHS, are illustrated. Furthermore, after basic concepts for the modelization of LCHS are formulated, two novel general-purpose information-processing modules are proposed and constructed, called perception cube and decision spheroid. Based on them, a novel block diagram based model is originally proposed and established for LCHS.

Fault-Tolerant Self Localization by Case-Based Reasoning

Abstract: In this article we present a case-based approach for the selflocalization of autonomous robots based on local visual information of landmarks. The goal is to determine the position and the orientation of the robot sufficiently enough, despite some strongly incorrect visual information. Our approach to solve this problem makes use of case-based reasoning methods.

Autonomous loop power flow control for distribution system

Abstract: This paper describes an autonomous control for loop power flow in a distribution system. The purpose of this study is to show that an autonomous method using local voltage information is able to distribute feeder power flow and to maintain the correct voltage with stable operations. The result of the authors' experiment clearly shows that the proposed autonomous method for loop power flow control balances the power flow and regulates the voltage with stable operations.

Interaction of perception and gaze control in autonomous vehicles

Abstract: For robust and secure behavior in natural environment an autonomous vehicle needs an elaborate vision sensor as main source of information The vision sensor must be adaptable to the external situation, the mission, the capabilities of the vehicle and the knowledge about the external world accumulated up to the present time In the EMS-Vision system, this vision sensor consists of four cameras with different focal lengths mounted on a highly dynamic pan-tilt camera head Image processing, gaze control and behavior decision interact with each other in a closed loop The image processing experts specify so-called regions of attention (RoAs) for each object in 3D object coordinates These RoAs should be visible with a resolution as required by the measurement techniques applied The behavior decision module specifies the relevance of obstacles like road segments, crossings or landmarks in the situation context The gaze control unit takes all this information in order to plan, optimize and perform a sequence of smooth pursuits, interrupted by saccades The sequence with the best information gain is performed The information gain depends on the relevance of objects or object parts, the duration of smooth pursuit maneuvers, the quality of perception and the number of saccades The functioning of the EMS-Vision system is demonstrated in a complex and scalable autonomous mission with the UBM test vehicle VAMORS

Comparison of three obstacle-avoidance methods for a mobile robot

Abstract: Obstacle avoidance is one of the most critical factors in the design of autonomous vehicles such as mobile robots. The purpose of this paper is to compare and contrast three different methods for obstacle detection and avoidance. These include fixed mounting of sonar sensors, a rotating sonar sensor and a laser scanner. The three systems have been installed on the BEARCAT mobile robot. Current work is ongoing and was tested in June 2001 at the International Ground Robotics Competition. This test bed system provides experimental evaluation of the tradeoffs among the systems in terms of resolution, range and computation speed as well as mounting arrangements. The significance of this work is in the increased understanding of obstacle avoidance for robot control and the applications of autonomous guided vehicle technology for industry, defense and medicine.

Fuzzy Range Sensor Filtering for Reactive Autonomous Robots

Abstract: This paper deals with the application of fuzzy logic to one of the navigational components of an indoor autonomous system implemented by means of intelligent agents. The most well known arguments supporting fuzzy control are the ability to cope with imprecise information in heuristic rule based knowledge and sensor measurements. Autonomous navigation based on ultrasonic sensors can provide an imprecise perception of the environment due to problems like crosstalking, noise and poor reliability. We propose a sensor fusion method based on history: the fuzzy sonar filtering.

Strange-Nonchaotic-Attractor-Like Behaviors in Coupled Map System*

Abstract: In a coupled map system, an attractor which seems to be strange nonchaotic attractor (SNA) is discovered for nonzero measure in parameter range. The attractor has nonpositive Lyapunov exponent (LE) and discrete structure. We call it strange-nonchaotic-attractor-like (SNA-like) behavior because the size of its discrete structure decreases with the computing precision increasing and the true SNA does not change. The SNA-like behavior in the autonomous system is born when the truncation error of round-off is amplified to the size of the discrete part of the attractor during the long time interval of positive local LE. The SNA-like behavior is easily mistaken for a true SNA judging merely from the largest LE and the phase portrait in double precision computing. In non-autonomous system an SNA-like attractor is also found.

On the stability of delay-differential systems in the behavioral framework

Abstract: In the behavioral approach, a linear time-invariant (LTI) delay-differential system is naturally introduced by Glusing-Luerssen (1997) as a continuous-time system whose dynamics are governed by a set of delay-differential equations, involving both painted and distributed delay operators. For this class of systems the notion of autonomy is introduced and characterized. Finally, asymptotic stability of autonomous delay-differential systems is investigated.

Truly random dynamics generated by autonomous dynamical systems

Abstract: We investigate explicit functions that can produce truly random numbers. We use the analytical properties of the explicit functions to show that a certain class of autonomous dynamical systems can generate random dynamics. This dynamics presents fundamental differences with the known chaotic systems. We present real physical systems that can produce this kind of random time-series. Some applications are discussed.

In flight autonomous system identification and control of MACE II using the frequency domain expert algorithm

Abstract: The Frequency Domain Expert (FDE) adaptive identification and control design algorithm will be applied to the M iddeck Active Control Experiment (MACE) during a re-flight of the experiment. FDE was recently developed by the authors to address the need for an algorithm that requires only local measurement, has predictable convergence properties, and yields performance in terms easily understood by controls system engineers. Ground testing to date has produced FDE controllers that reduce line-of-sight error by more than 22 dB, only a few dB less than the best performance attained via offline, fixed-gain LQG controllers during the original MACE flight.

Suitable Strategies for In-plane Orbit Acquisition using Micro-thrusters

Abstract: The deviations in the injection orbital parameters, resulting from launcher dispersions, need to be corrected through a set of acquisition maneuvers to achieve the desired nominal parameters. When multiple satellites are injected into a single orbital plane, as a part of constellation establishment, they have to positioned in the plane with appropriate semi-major axis ‘a’ and mean anomaly ‘M’. In this paper, three strategies are studied for achieving orbit acquisition. The first strategy is by deriving an analogy to the Linear Quadratic Regulator (LQR). The state dynamics and the control law are of the form U X X B A + = & and X U K − = . The feedback gain K is calculated by minimizing the cost function. Under this strategy the thrust (N) and velocity increment ( V ∆ ) are functions of time and only the matrix K needs to be up-linked. Any revision in the current or the target states, will then lead to a simple re-calculation of K and up-linking them. The second strategy assumes that V ∆ is same for each maneuver and calculates the number of maneuvers and the V ∆ required for each maneuver. If the maneuvers are stopped for reasons like orbit assessment, and thruster performance evaluation, the strategy can be restarted easily without having any penalty on the overall V ∆ . Besides these two strategies, a third strategy based on the application of Fuzzy Modified Potential Function is also studied for autonomous orbit acquisition with constraints in the path. By adding Fuzzy logic to the potential function it is shown that, maneuvers can be changed gradually ahead of the constraints. Onboard implementation related aspects are also briefly addressed for all the strategies. Introduction Due to the increasing cost of the ground operations, worldwide interest is towards autonomy in spacecraft operations. Thanks to the recent advances in VLSI and MEMS technologies, onboard autonomy is becoming a reality. Missions like PROBA (Project for Onboard Autonomy), as the name suggests, are aimed at demonstrating the autonomous operations in space. A fully autonomous system would make use measurements that are from passive sources and carryout estimation and control with no dependence on ground systems. The autonomy could be in terms of house keeping operations, attitude control and finally orbit control and maintenance. Autonomous orbit control or maintenance is a mission critical operation as it involves fuel expenditure and any unexpected anomaly can lead to mission catastrophes. Any autonomous orbit correction strategy should therefore have very small corrections at each step and be able to revise the strategy with minimal cost on the total fuel. Besides the advances in technology, many launchers are now offering piggyback launches for micro and nano-satellites. This has enabled many academic institutions to take up design and development of small satellites. Towards

Self-referential structure in collective agent system. ii, carrier sequence control of agv transportation system based on diversity- regulation of strategy

Abstract: This paper focuses on a large scale distributed autonomous system in a dynamic environment. It proposes a dynamically reconfigurable formation which functions as the autonomous conveyance order formation of in an automated guided vehicle (AGV) system. Adaptable parameters to the dynamic environment are shown to be found using a distribution of "self-organizing velocity".

Persistence in systems of asymptotically autonomous difference equations

Abstract: Asymptotically autonomous dynamical systems, both continuous and discrete, arise in the study of physical and biological systems that are modeled with explicit time-dependenceConvergence properties of such dynamical systems can be used to simplify analysis In this paper, results are derived concerning the limiting behavior of a general asymptotically autonomous system of difference equations and its relationship to the dynamics of its limiting system Examples from the biological literature are given

Strange—Nonchaotic—Attractor—Like Behaviors in Coupled Map SYstems

Abstract: In a coupled map system, an attractor which seems to be strange nonchaotic attractor (SNA) is discovered for nonzero measure in parameter range The attractor has nonpositive Lyapunov exponent (LE) and discrete structure We call it strange-nonchaotic-attractor-like (SNA-like) behavior because the size of its discrete structure eleoreases with the computing precision increasing and the true SNA does not change The SNA-like behavior in the autonomous system is born when the truncation error of round-off is amplified to the size of the discrete part of the attractor during the long time interval of positive local LE The SNA-like behavior is easily mistaken for a true SNA judging merely from the largest LE and the phase portrait in double precision computing In non-autonomous system an SNA-like attractor is also found

Effective Planning Horizons for Robust Autonomy

Abstract: Robust autonomy, in the sense of performing tasks in the face of dynamic changes to the environment, requires that an autonomous system be capable of responding appropriately to such changes. One such response is to effectively adapt the allocation of resources from planning to execution. By adapting the resource allocation between deliberation and execution, an autonomous system can produce shorter plans more frequently in environments with high levels of uncertainty, while producing longer, more complex plans when the environment offers the opportunity to successfully execute complex plans. In this paper we propose the idea of the “effective planning horizon” which adapts to environmental changes to bound the deliberation in an interleaved planning/execution system. The effective planning horizon is developed from an analysis of the advantages and disadvantages of three classic autonomous system architectures as feedback control systems. This leads to the development of an analytic model which suggests the use of maximizing the expected value of plans by adjusting the planning horizon.

Achievability for telerobotic systems

Abstract: Methods are needed to improve the capabilities of autonomous robots to perform tasks that are difficult for contemporary robots, and to identify those tasks that robots cannot perform. Additionally, in the realm of remote handling, methods are needed to assess which tasks and/or subtasks are candidates for automation. We are developing a new approach to understanding the capability of autonomous robotic systems. This approach uses formalized methods for determining the achievability of tasks for robots, that is, the likelihood that an autonomous robot or telerobot can successfully complete a particular task. Any autonomous system may be represented in achievability space by the volume describing that system’s capabilities within the 3-axis space delineated by perception, cognition, and action. This volume may be thought of as a probability density with achievability decreasing as the distance from the centroid of the volume increases. Similarly, any task may be represented within achievability space. Howe...

A Qualitative System as a Frame to Control Unmanned Vehicles

Abstract: It is known that the techniques bracketed under the topic of Soft Computing have a strong capability of learning and cognition joint to a good tolerance with uncertainty and imprecision. Due to these properties they can be applied successfully in Intelligent Vehicles Systems. In particular Fuzzy Logic is very adequate to build qualitative or linguistic models of many kinds of systems. The aim of this paper is to integrate in a qualitative model the vehicle operation and the driver behavior in such a way that an unmanned guiding system can be developed around it [2] [6].

Autonomous control systems: applications to remote sensing and image processing

Abstract: One of the main challenges of any control (or image processing) paradigm is being able to handle complex systems under unforeseen uncertainties. A system may be called complex here if its dimension (order) is too high and its model (if available) is nonlinear, interconnected, and information on the system is uncertain such that classical techniques cannot easily handle the problem. Examples of complex systems are power networks, space robotic colonies, national air traffic control system, and integrated manufacturing plant, the Hubble Telescope, the International Space Station, etc. Soft computing, a consortia of methodologies such as fuzzy logic, neuro-computing, genetic algorithms and genetic programming, has proven to be powerful tools for adding autonomy and semi-autonomy to many complex systems. For such systems the size of soft computing control architecture will be nearly infinite. In this paper new paradigms using soft computing approaches are utilized to design autonomous controllers and image enhancers for a number of application areas. These applications are satellite array formations for synthetic aperture radar interferometry (InSAR) and enhancement of analog and digital images.