Showing papers on "Autonomous system (mathematics) published in 2010"

Optimal trajectory generation for dynamic street scenarios in a Frenét Frame

Abstract: Safe handling of dynamic highway and inner city scenarios with autonomous vehicles involves the problem of generating traffic-adapted trajectories. In order to account for the practical requirements of the holistic autonomous system, we propose a semi-reactive trajectory generation method, which can be tightly integrated into the behavioral layer. The method realizes long-term objectives such as velocity keeping, merging, following, stopping, in combination with a reactive collision avoidance by means of optimal-control strategies within the Frenet-Frame [12] of the street. The capabilities of this approach are demonstrated in the simulation of a typical high-speed highway scenario.

A four-wing hyper-chaotic attractor and transient chaos generated from a new 4-D quadratic autonomous system

Abstract: This paper presents a new four-dimensional (4-D) smooth quadratic autonomous chaotic system, which can present periodic orbit, chaos, and hyper-chaos under the conditions on different parameters. Importantly, the system can generate a four-wing hyper-chaotic attractor and a pair of coexistent double-wing hyper-chaotic attractors with two symmetrical initial conditions. Furthermore, a four-wing transient chaos occurs in the system. The dynamic analysis approach- in the paper involves time series, phase portraits, Poincare maps, bifurcation diagrams, and Lyapunov exponents, to investigate some basic dynamical behaviors of the proposed 4-D system.

Recent developments in dynamical systems: three perspectives

Abstract: This paper aims to an present account of some problems considered in the past years in Dynamical Systems, new research directions and also provide some open problems.

Learning for Autonomous Navigation

Abstract: Autonomous navigation by a mobile robot through L natural, unstructured terrain is one of the premier k challenges in field robotics. Tremendous advances V in autonomous navigation have been made recently in field robotics. Machine learning has played an increasingly important role in these advances. The Defense Advanced Research Projects Agency (DARPA) UGCV-Perceptor Integration (UPI) program was conceived to take a fresh approach to all aspects of autonomous outdoor mobile robot design, from vehicle design to the design of perception and control systems with the goal of achieving a leap in performance to enable the next generation of robotic applications in commercial, industrial, and military applications. The essential problem addressed by the UPI program is to enable safe autonomous traverse of a robot from Point A to Point B in the least time possible given a series of waypoints in complex, unstructured terrain separated by 0.2-2 km. To accomplish this goal, machine learning techniques were heavily used to provide robust and adaptive performance, while simultaneously reducing the required development and deployment time. This article describes the autonomous system, Crusher, developed for the UPI program and the learning approaches that aided in its successful performance.

Existence of pullback attractors for pullback asymptotically compact processes

Abstract: This paper is concerned with the existence of pullback attractors for evolution processes. Our aim is to provide results that extend the following results for autonomous evolution processes (semigroups) (i) An autonomous evolution process which is bounded, dissipative and asymptotically compact has a global attractor. (ii) An autonomous evolution process which is bounded, point dissipative and asymptotically compact has a global attractor. The extension of such results requires the introduction of new concepts and brings up some important differences between the asymptotic properties of autonomous and non-autonomous evolution processes. An application to damped wave problem with non-autonomous damping is considered.

An Autonomous Mobile Robotics Testbed: Construction, Validation, and Experiments

Abstract: This paper describes design and construction of an Autonomous Mobile Robotics Systems Testbed in detail. The testbed is an indoor experimental platform for developing and validating theoretical as well as practical research work in identification, coordinative and cooperative control, trajectory generation, computational intelligence, and sensing for multiple autonomous mobile robotics systems. It provides a designated space for multiple mobile robots while tracking their position and orientation in real-time using an overhead vision system. Several problems encountered in developing the testbed such as multi-camera color consistency, radial lens distortion, hat pattern design are clearly addressed. The testbed is analyzed for its performance and several experiments with ER1 mobile robots are presented.

On the Benefits of In-Flight System Identification for Autonomous Airdrop Systems

Abstract: A unique feature of airdrop systems is the inherent and large variability in flight dynamic characteristics The same physical article dropped on two different occasions will exhibit significantly different dynamic response The problem only becomes worse for different test articles Control systems for autonomous airdrop systems explicitly or implicitly assume knowledge of the flight dynamic characteristics in some way, shape, or form A question facing autonomous airdrop designers is whether to use precomputed dynamic characteristics inside the control law, or to compute the needed flight dynamic characteristics in-flight and subsequently employ them in the control law This paper establishes conditions when in-flight identified characteristics, with a focus on the turn rate dynamics, should be used, and when it is better to use precomputed results It is shown that with expected levels of system variability, sensor noise, and atmospheric wind, in-flight identification generally produces significantly more accurate dynamic behavior of the lateral dynamics than a precomputed model of the nominal system, even when the in-flight identification is performed with highly inaccurate sensor data The only exception to this rule observed in this work is the situation where atmospheric winds are high and a direct heading measurement is not available In this situation, a precomputed estimate of the time constant of the lateral dynamics is more accurate than an in-flight estimate These conclusions are reached though a comprehensive simulation study using a validated airdrop flight dynamic model applied to both a small and large parafoil

Multi-sensor surveillance of indoor environments by an autonomous mobile robot

Abstract: An autonomous mobile robotic system for surveillance of indoor environments is presented. Applications of the proposed system include surveillance of large environments such as airports, museums and warehouses. A multi-layer decision scheme controls different surveillance tasks. In particular, this paper focuses on two main functions: building an augmented map of the environment and monitoring specific areas of interest to detect unexpected changes based on visual and laser data. The effectiveness of the system is demonstrated through experimental tests. The results are promising, proving the proposed methods to be successful in detecting either new or removed objects in the surveyed scene. It is also shown that the robotic surveillance system is able to address a number of specific problems related to environment mapping, autonomous navigation and scene processing, and could be effectively employed for real-world surveillance applications.

A novel one equilibrium hyper-chaotic system generated upon Lü attractor

Abstract: By introducing an additional state feedback into a three-dimensional autonomous chaotic attractor Lu system, this paper presents a novel four-dimensional continuous autonomous hyper-chaotic system which has only one equilibrium. There are only 8 terms in all four equations of the new hyper-chaotic system, which may be less than any other four-dimensional continuous autonomous hyper-chaotic systems generated by three-dimensional (3D) continuous autonomous chaotic systems. The hyper-chaotic system undergoes Hopf bifurcation when parameter c varies, and becomes the 3D modified Lu system when parameter k varies. Although the hyper-chaotic system does not undergo Hopf bifurcation when parameter k varies, many dynamic behaviours such as periodic attractor, quasi periodic attractor, chaotic attractor and hyper-chaotic attractor can be observed. A circuit is also designed when parameter k varies and the results of the circuit experiment are in good agreement with those of simulation.

Integrated automation system

Abstract: Autonomous operations are conducted within a defined geographical region. In an autonomous system of a management party a plurality of localised zones are established having operation-defined geographical boundaries within the geographical region. Entities having autonomous operating systems to perform specific autonomous operations within respective ones of the localised zones. The autonomous system of the management party is integrated with the autonomous operating systems of the entities.

Dynamics of WIP Regulation in Large Production Networks of Autonomous Work Systems

Abstract: In this paper, dynamic behavior is compared for two methods of local work in progress (WIP) regulation in autonomous work systems in production networks. In one method, work systems do not share information regarding the expected physical flow of orders between them; in the other, order-flow information is shared to compensate for the variable dynamic effects of physical order-flow coupling. In both methods, the work systems adjust production rate with the objective of maintaining a desired amount of local WIP. A linear discrete-time dynamic model of the flow of orders between work systems is used, which promotes identification of fundamental properties such as characteristic times and damping. The results demonstrate the need for order-flow information sharing in establishing desired network dynamic behavior. Examples are used to illustrate behavior in the general case of omnidirectional order flows and the special case of unidirectional order flows.

Interactive method for autonomous microsystem design

Abstract: This paper describes a multidisciplinary and interactive approach for the design of autonomous microsystems. These devices satisfy the actual requirements in terms of size, cost and autonomy. This autonomy is obtained by harvesting the energy in microsystem environment. There is no denying that microsystem design requires multidisciplinary skills and necessitates collaboration between several groups with different fields of expertise. All aspects have to be considered to get a mechanically, electronically and energetically efficient structure, consistent with the specifications and the requirements of the problem. However, few designers are competent enough in all the involved engineering fields. Thereby, we propose a multidisciplinary and interactive approach for autonomous microsystem design. This method delves into several steps. It begins by a global description and analysis of the system in its environment. This problem structuring is mainly based on the use of tools of functional analysis. Then, the autonomous microsystem is modeled, with a special care on energy harvester design. The method is applied to energy harvester design for automotive braking system instrumentation. The interactive character is present through the consideration of interactions (cognitive, physical and sensory). Finally, the multidisciplinary aspect is ensured by the collaboration and the exchanges between designers and numeric tools.

Application of a three-component evaluation system for autonomous control in logistics

Abstract: Autonomous control of logistic systems is a potential solution to the problems encountered in modern competitor marketplaces Autonomous control in a logistic system is characterized by the

On Low Complexity Predictive Approaches to Control of Autonomous Vehicles

Abstract: In this chapter we present low complexity predictive approaches to the control of autonomous vehicles. A general hierarchical architecture for fully autonomous vehicle guidance systems is presented together with a review of two control design paradigms. Our review emphasizes the trade off between performance and computational complexity at different control levels of the architecture. In particular, experimental results are presented, showing that if the controller at the lower level is properly designed, then it can handle system nonlinearities and model uncertainties even if those are not taken into account at the higher level.

Whose Goal is it anyway? User Interaction in an Autonomous System

Abstract: We describe how establishing goals at different levels of abstraction helps a human operator to supervise/control aion helps a human operator to supervise/control a system consisting of multiple unmanned air vehicles. In particular we focus on the importance of including Human Machine Interaction within the design of an autonomous system. Important lessons include being explicit about the level of authority to delegate to the automated part of the system and viewing the interaction between the human and the automated planning / execution system as a partnership, thus facilitating a shared awareness of, and commitment to,

Interacting with Adaptive Systems

Abstract: This chapter concerns user responses toward adaptive and autonomous system behavior. The work consists of a review of the relevant literature off-set with the findings from three studies that investigated the way people respond to adaptive and autonomous agents. The systems evaluated in this chapter make decisions on behalf of the user, behave autonomously and need user feedback or compliance. Apart from the need for systems to competently perform their tasks, people will see adaptive and autonomous system behavior as social actions. Factors from humans’ social interaction will therefore also play a role in the experience users will have when using the systems. The user needs to trust, understand and control the system’s autonomous actions. In some cases the users need to invest effort in training the system so that it can learn. This indicates a complex relationship between the user, the adaptive and autonomous system and the specific context in which the system is used. This chapter specifically evaluates the way people trust and understand a system as well as the effects of system transparency and autonomy.

Attractor of Smale - Williams type in an autonomous time-delay system

Abstract: We propose an example of smooth autonomous system governed by differential delay equation manifesting chaotic dynamics apparently associated with hyperbolic attractor of Smale - Williams type. The general idea is to depart from a system generating successive pulses of oscillations, each of which gives rise to the next one with transformation of the phase in accordance with chaotic Bernoulli map. From mathematical point of view, it is an infinite-dimensional system due to presence of the time delay. Nevertheless, the material we present gives a foundation to assert that the model delivers an example of a small-dimensional hyperbolic strange attractor, embedded in the infinite-dimensional phase space.

Coarse-Graining Autonomous ODE Systems by Inducing a Separation of Scales: Practical Strategies and Mathematical Questions

Abstract: This short note introduces a methodology for sequential multiscale modeling of autonomous, “microscopic”, systems of Ordinary Differential Equations through a redefinition of the original dynamics as an augmented system with an explicit separation of time scales arising merely from the definition of time-averaging. Associated mathematical questions are stated and discussed.

Efficient Sensor Signal Filtering for Autonomous Wireless Nodes

Abstract: Wireless sensor networks are nowadays a reality. However, a wireless node must be a truly autonomous system, i.e., it must embed its own power source, which is generally a battery pack. For this reason, it is of main concern to limit every source of wasted power. In particular, nodes exploit low-duty-cycle strategies to increase their life, spending most of their time in low-power mode, turning off all devices within the system except a wake-up oscillator. However, this way, some time must be spent waiting for the circuitry settling time, particularly if a high-accuracy measurement is required. In this paper, an efficient implementation of a filtering algorithm that is able to reduce this time is discussed. It is based on a hybrid combination of a median and a mean filter, joining the advantages of both linear and nonlinear filtering. A well-tailored implementation has experimentally been tested and discussed. Two wireless prototypes have been realized to test the proposed filter performance for temperature and humidity measurements. The experimental results permit comparing the implemented filters in terms of computational time, power consumption, and the performance of noise filtering. For both sensors, the new filtering strategy resulted to be more efficient in terms of noise removal and consumption than traditional algorithms. In particular, in the case of slow sensors such as a humidity one, delays are dictated by the sensor itself, and computational time can be neglected, while for fast sensors such as a temperature one, the proposed schema greatly improves the system update rate.

Hyperchaos in a New Four-Dimensional Autonomous System

Abstract: In this letter we report a new four-dimensional autonomous system, constructed from a chaotic Lorenz system by introducing an adequate feedback controller to the third equation. We show that when parameters are conveniently chosen, the control method can drive the chaotic Lorenz system to hyperchaotic regions. Analytical and numerical procedures are conducted to study the dynamical behaviors of the proposed new system.

Solving Zhou's chaotic system using Euler's method

Abstract: An algorithm for Euler’s method is used to obtain an approximation for the initial-value problem for ordinary differential equation. This method is then employing to Zhou’s chaotic system. This system is a three-dimensional autonomous system according to the numerical simulation as well as the theoretical analysis. We use the C++ software to solve this system and MATLAB to plot the solutions and the results are given for different number of iterations.

A new set of admitted transformations for autonomous stochastic ordinary differential equations

Abstract: This paper investigates symmetries of autonomous ordinary stochastic differential equations. Change of time includes the stochastic process itself, and is uniquely determined by the transformation of the spatial variable. As a particular feature, the time change by an admitted Lie symmetry group may be unrelated with the time change in the stochastic process. Sufficient conditions for a Lie group to be admitted by an autonomous equation are derived. This method can be applied to second order autonomous equations as well as systems of autonomous stochastic differential equations.

Safe Navigation for Autonomous Vehicles in Dynamic Environments: an Inevitable Collision State (ICS) Perspective

Abstract: This thesis deals with the problem of safe navigation for autonomous vehicles in dynamic environments. Motion safety is defined by means of Inevitable Collision States (ICS). An ICS is a state for which, no matter what the future trajectory of the vehicle is, a collision eventually occurs. For obvious safety reasons, an autonomous system should never ever find itself in one of such states. To accomplish this objective the problem is addressed in two parts. The first part focuses on determining which states are safe for the vehicle (non-ICS). The second part concentrates on how to select a valid control to move from one safe state to the other. Once it is found, the vehicle can apply it to successfully navigate the environment. Simulations and experimental results are presented to validate the approach.

Task-switching for self-sufficient robots

Abstract: Task-switching enables a system to make its own decisions about which task to perform. It is therefore a key ability for any truly autonomous system. Common task-switching methods range from computationally expensive planning methods to often suboptimal, minimalistic, heuristics. This thesis takes a bio-inspired approach, motivated by the fact that animals successfully make task-switching decisions on a daily basis. The field of behavioural ecology provides a vast literature on animal task-switching. Generally these works are descriptive models of animal behaviour, either modelling to fit the data from observed animal behaviour, or theoretically optimal models of how animals ought to behave. But what is needed in robotics are methods that generate behaviour based on the information available (due to sensing) to the robot. Furthermore these methods have to take the physical limitations (velocity, acceleration, storage capacity etc.) of the robot into account. This thesis takes inspiration from descriptive behavioural ecology models and proposes a situated and embodied task-switching method suitable for mobile robots. To evaluate the quality of the decisions an objective function is needed. Reproductive success is commonly used in Biology, here economical success is used. We illustrate the applicability of the proposed methods on Toda's Fungus Eater robot. The decisions this robot faces are (1) when to work and when to refuel and (2) where to work or refuel respectively. Both decision types are essential to any autonomous, mobile robot. The proposed task-switching methods are based on Optimal Foraging Theory, in particular on rate-maximization and the Marginal-Value Theorem.

Quantifying Distributed System Stability through Simulation: A Case Study of an Agent-Based System for Flow Reconstruction of DDoS Attacks

Abstract: We investigate the stability properties of a novel agent-based system for the detection of network bandwidth-based distributed denial of service (DDoS) attacks. The proposed system provides a description of the structure of flows which comprise the DDoS attack. In doing so, it facilitates DDoS mitigation at or near attack traffic sources. The constituent agents within the system operate at the inter autonomous system (AS) level, comprising a distributed collection of IP-layer network taps which self-organize in response to attack flows. We formalize the notion of stability for the proposed system, and show how we can use simulation to identify regions of instability within the system’s parameter space. We then modify our system design to circumvent the uncovered singularities, and demonstrate the efficacy and tradeoffs implicit in our redesigned system.