Metaheuristic approaches to the hybrid flow shop scheduling problem with a cost-related criterion

In the paper, the flow-shop scheduling problem with parallel machines at each stage (machine center) is studied. For each job its release and due date as well as a processing time for its each operation are given. The scheduling criterion consists of three parts: the total weighted earliness, the total weighted tardiness and the total weighted waiting time. The criterion takes into account the costs of storing semi-manufactured products in the course of production and ready-made products as well as penalties for not meeting the deadlines stated in the conditions of the contract with customer. To solve the problem, three constructive algorithms and three metaheuristics (based one Tabu Search and Simulated Annealing techniques) are developed and experimentally analyzed. All the proposed algorithms operate on the notion of so-called operation processing order, i.e. the order of operations on each machine. We show that the problem of schedule construction on the base of a given operation processing order can be reduced to the linear programming task. We also propose some approximation algorithm for schedule construction and show the conditions of its optimality.

Experimental investigation of a turbulent reacting plume

An experimental investigation has been made of a round, non-buoyant plume of nitric oxide, NO, in a turbulent grid flow of ozone, 03, using the Turbulent Smog Chamber at the University of Sydney. The measurements have been made at a resolution not previously reported in the literature. The reaction is conducted at non-equilibrium so there is significant interaction between turbulent mixing and chemical reaction. The plume has been characterized by a set of constant initial reactant concentration measurements consisting of radial profiles at various axial locations. Whole plume behaviour can thus be characterized and parameters are selected for a second set of fixed physical location measurements where the effects of varying the initial reactant concentrations are investigated. Careful experiment design and specially developed chemilurninescent analysers, which measure fluctuating concentrations of reactive scalars, ensure that spatial and temporal resolutions are adequate to measure the quantities of interest. Conserved scalar theory is used to define a conserved scalar from the measured reactive scalars and to define frozen, equilibrium and reaction dominated cases for the reactive scalars. Reactive scalar means and the mean reaction rate are bounded by frozen and equilibrium limits but this is not always the case for the reactant variances and covariances. The plume reactant statistics are closer to the equilibrium limit than those for the ambient reactant. The covariance term in the mean reaction rate is found to be negative and significant for all measurements made. The Toor closure was found to overestimate the mean reaction rate by 15 to 65%. Gradient model turbulent diffusivities had significant scatter and were not observed to be affected by reaction. The ratio of turbulent diffusivities for the conserved scalar mean and that for the r.m.s. was found to be approximately 1. Estimates of the ratio of the dissipation timescales of around 2 were found downstream. Estimates of the correlation coefficient between the conserved scalar and its dissipation (parallel to the mean flow) were found to be between 0.25 and the significant value of 0.5. Scalar dissipations for non-reactive and reactive scalars were found to be significantly different. Conditional statistics are found to be a useful way of investigating the reactive behaviour of the plume, effectively decoupling the interaction of chemical reaction and turbulent mixing. It is found that conditional reactive scalar means lack significant transverse dependence as has previously been found theoretically by Klimenko (1995). It is also found that conditional variance around the conditional reactive scalar means is relatively small, simplifying the closure for the conditional reaction rate. These properties are important for the Conditional Moment Closure (CMC) model for turbulent reacting flows recently proposed by Klimenko (1990) and Bilger (1993). Preliminary CMC model calculations are carried out for this flow using a simple model for the conditional scalar dissipation. Model predictions and measured conditional reactive scalar means compare favorably. The reaction dominated limit is found to indicate the maximum reactedness of a reactive scalar and is a limiting case of the CMC model. Conventional (unconditional) reactive scalar means obtained from the preliminary CMC predictions using the conserved scalar p.d.f. compare favorably with those found from experiment except where measuring position is relatively far upstream of the stoichiometric distance. Recommendations include applying a full CMC model to the flow and investigations both of the less significant terms in the conditional mean species equation and the small variation of the conditional mean with radius. Forms for the p.d.f.s, in addition to those found from experiments, could be useful for extending the CMC model to reactive flows in the atmosphere.

Obstacle detection using optical flow

Motion has been examined in biology to be a critical component for obstacle avoidance and navigation. In particular, optical flow is a powerful motion cue that has been exploited in many biological systems for survival. In this paper, we investigate an obstacle detection system that uses optical flow to obtain range information to objects. Our experimental results demonstrate that optical flow is capable of providing good obstacle information but has obvious failure modes. We acknowledge that our optical flow system has certain disadvantages and cannot be solely used for navigation. Instead, we believe that optical flow is a critical visual subsystem used when moving at reason- able speeds. When combined with other visual subsystems, considerable synergy can result.

Learning to avoid indoor obstacles from optical flow

Optical flow (OF) is a powerful motion cue that captures the fusion of two important properties for the task of obstacle avoidance − 3D self-motion and 3D environmental surroundings. The problem of extracting such information for obstacle avoidance is commonly addressed through quantitative techniques such as time-to-contact and divergence, which are highly sensitive to noise in the OF image. This paper presents a new strategy towards obstacle avoidance in an indoor setting, using the combination of quantitative and structural properties of the OF field, coupled with the flexibility and efficiency of a machine learning system.The resulting system is able to effectively control the robot in real-time, avoiding obstacles in familiar and unfamiliar indoor environments, under given motion constraints. Furthermore, through the examination of the networks internal weights, we show how OF properties are being used toward the detection of these indoor obstacles.

Virtual force feedback teleoperation of the InsectBot using optical flow

This paper proposes the use of optical flow from a moving robot to provide force feedback to an operator’s joystick to facilitate collision free teleoperation. Optical flow is measured by a pair of wide angle cameras on board the vehicle and used to generate a virtual environmental force that is reflected to the user through the joystick, as well as feeding back into the control of the vehicle. We show that the proposed control is dissipative and prevents the vehicle colliding with the environment as well as providing the operator with a natural feel for the remote environment. Experimental results are provided on the InsectBot holonomic vehicle platform.

A new framework for force feedback teleoperation of robotic vehicles based on optical flow

This paper proposes the use of optical flow from a moving robot to provide force feedback to an operator's joystick to facilitate collision free teleoperation. Optic flow is measured by wide angle cameras on board the vehicle and used to generate a virtual environmental force that is reflected to the user through the joystick, as well as feeding back into the control of the vehicle. The coupling between optical flow (velocity) and force is modelled as an impedance - in this case an optical impedance. We show that the proposed control is dissipative and prevents the vehicle colliding with the environment as well as providing the operator with a natural feel for the remote environment. The paper focuses on applications to aerial robotics vehicles, however, the ideas apply directly to other force actuated vehicles such as submersibles or space vehicles, and the authors believe the approach has potential for control of terrestrial vehicles and even teleoperation of manipulators. Experimental results are provided for a simulated aerial robot in a virtual environment controlled by a haptic joystick.

Dynamic Image-based visual servo control using centroid and optic flow features

This paper considers the question of designing a fully image-based visual servo control for a class of dynamic systems. The work is motivated by the ongoing development of image-based visual servo control of small aerial robotic vehicles. The kinematics and dynamics of a rigid-body dynamical system (such as a vehicle airframe) maneuvering over a flat target plane with observable features are expressed in terms of an unnormalized spherical centroid and an optic flow measurement. The image-plane dynamics with respect to force input are dependent on the height of the camera above the target plane. This dependence is compensated by introducing virtual height dynamics and adaptive estimation in the proposed control. A fully nonlinear adaptive control design is provided that ensures asymptotic stability of the closed-loop system for all feasible initial conditions. The choice of control gains is based on an analysis of the asymptotic dynamics of the system. Results from a realistic simulation are presented that demonstrate the performance of the closed-loop system. To the author's knowledge, this paper documents the first time that an image-based visual servo control has been proposed for a dynamic system using vision measurement for both position and velocity.

Combined optic-flow and stereo-based navigation of urban canyons for a UAV

We present a novel vision-based technique for navigating an Unmanned Aerial Vehicle (UAV) through urban canyons. Our technique relies on both optic flow and stereo vision information. We show that the combination of stereo and optic-flow (stereo-flow) is more effective at navigating urban canyons than either technique alone. Optic flow from a pair of sideways-looking cameras is used to stay centered in a canyon and initiate turns at junctions, while stereo vision from a forward-facing stereo head is used to avoid obstacles to the front. The technique was tested in full on an autonomous tractor at CSIRO and in part on the USC autonomous helicopter. Experimental results are presented from these two robotic platforms operating in outdoor environments. We show that the autonomous tractor can navigate urban canyons using stereoflow, and that the autonomous helicopter can turn away from obstacles to the side using optic flow. In addition, preliminary results show that a single pair of forward-facing fisheye cameras can be used for both stereo and optic flow. The center portions of the fisheye images are used for stereo, while flow is measured in the periphery of the images.

Specifying and enforcing a fine-grained information flow policy : model and experiments

In this paper we present a model for defining and enforcing a fine-grained information flow policy. We describe how the policy can be enforced on a typical computer and present experiments using the proposed model. A key feature of the model is that it allows the expression of rules which detail precisely which information elements are allowed to mix together. For example, the model allows the expression of a policy which forbids a doctor from mixing the personal medical details of the patients. The enforcement mechanisms tracks and records information flows within the system so that dynamic changes to the policy can be made with respect to information elements which may have propagated to different locations in the system.

Active flow control bump design using hybrid Nash-game coupled to evolutionary algorithms

In this paper, the optimal design of an active flow control device; Shock Control Bump (SCB) on suction and pressure sides of transonic aerofoil to reduce transonic total drag is investigated. Two optimisation test cases are conducted using different advanced Evolutionary Algorithms (EAs); the first optimiser is the Hierarchical Asynchronous Parallel Evolutionary Algorithm (HAPMOEA) based on canonical Evolutionary Strategies (ES). The second optimiser is the HAPMOEA is hybridised with one of well-known Game Strategies; Nash-Game. Numerical results show that SCB significantly reduces the drag by 30% when compared to the baseline design. In addition, the use of a Nash-Game strategy as a pre-conditioner of global control saves computational cost up to 90% when compared to the first optimiser HAPMOEA.