Particle Swarm Optimization (PSO) is a population based heuristic search method for finding global optimal values in multi-disciplinary design optimization problems. PSO is based on simple social behavior exhibited by...
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ISBN:
(纸本)1563478927
Particle Swarm Optimization (PSO) is a population based heuristic search method for finding global optimal values in multi-disciplinary design optimization problems. PSO is based on simple social behavior exhibited by birds and insects. Due to its simplicity in implementation, PSO has been increasingly gaining popularity in the optimization community. Previous work by the authors demonstrated superior design space search capabilities of particle swarm through implementing digital pheromones in a regular PSO. Although preliminary results showed substantial performance gains, a quantitative assessment has not yet been made to prove the claim. Through a formal statistical hypothesis testing, this paper attempts to evaluate the performance characteristics of PSO with digital pheromones. Specifically, the authors' claim that the use of digital pheromones improves the solution quality and solution times are tested using various multi-dimensional unconstrained optimization test problems. Conclusions are drawn based on the results from statistical analysis of these test problems and presented in the paper.
Military operations are turning to more complex and advanced automation technology for minimum risk and maximum efficiency. A critical piece to this strategy is unmanned aerial vehicles (UAVs). UAVs require the intell...
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ISBN:
(纸本)1563478927
Military operations are turning to more complex and advanced automation technology for minimum risk and maximum efficiency. A critical piece to this strategy is unmanned aerial vehicles (UAVs). UAVs require the intelligence to safely maneuver along a path to an intended target, avoiding obstacles such as other aircrafts or enemy threats. Often automated path planning algorithms are employed to specify targets for a UAV to fly to. To date, path-planning algorithms have been limited to two-dimensional problem formulations. This paper presents a unique three-dimensional path planning problem formulation and solution approach using Particle Swarm Optimization (PSO). The problem formulation was designed to minimize risk due to enemy threats and also to minimize fuel consumption incurred by deviating from the original path. In addition, a third objective in the problem formulation takes into account reconnaissance targets. The initial design point is defined as the original path of the UAV. Using PSO, alternate paths are generated using B-spline curves, optimized based on preferences set for the three objectives. The resulting paths can be optimized with a preference towards maximum safety, minimum fuel consumption, or target reconnaissance. The problem formulation and solution implementation is described along with the results from several simulated scenarios.
Service-Learning (S-L) and engineering education share the common goals of relating theory to practice and of civic engagement ("public problem solving"). In the current effort, service-learning is being int...
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This paper introduces an emotion interaction system for a service robot. The purpose of emotion interaction systems in service robots is to make people feel that the robot is not a mere machine, but reliable living as...
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This paper introduces an emotion interaction system for a service robot. The purpose of emotion interaction systems in service robots is to make people feel that the robot is not a mere machine, but reliable living as...
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This paper introduces an emotion interaction system for a service robot. The purpose of emotion interaction systems in service robots is to make people feel that the robot is not a mere machine, but reliable living assistant in the home. The emotion interaction system is composed of the emotion recognition, generation, and expression systems. A user's emotion is recognized by multi-modality, such as voice, dialogue, and touch. The robot's emotion is generated according to a psychological theory about emotion: OCC (Ortony, Clore, and Collins) model, which focuses on the user's emotional state and the information about environment and the robot itself. The generated emotion is expressed by facial expression, gesture, and the musical sound of the robot. Because the proposed system is composed of all the three components that are necessary for a full emotional interaction cycle, it can be implemented in the real robot system and be tested. Even though the multi- modality in emotion recognition and expression is still in its rudimentary stages, the proposed system is shown to be extremely useful in service robot applications. Furthermore, the proposed framework can be a cornerstone for the design of emotion interaction and generation systems for robots.
Military operations are turning to more complex and advanced automation technology for minimum risk and maximum efficiency. A critical piece to this strategy is unmanned aerial vehicles (UAVs'). UAVs require the i...
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ISBN:
(纸本)1563478234
Military operations are turning to more complex and advanced automation technology for minimum risk and maximum efficiency. A critical piece to this strategy is unmanned aerial vehicles (UAVs'). UAVs require the intelligence to safely maneuver along a path to an intended target, avoiding obstacles such as other aircrafts or enemy threats. Often automated path planning algorithms are employed to specify targets for a UAV to fly to. To date, path-planning algorithms have been limited to two-dimensional problem formulations. This paper presents a unique three-dimensional path planning problem formulation and solution approach using Particle Swarm Optimization (PSO). The problem formulation was designed to minimize risk due to enemy threats while simultaneously minimizing fuel consumption. The initial design point is a straight path between the current position and the desired target. Using PSO, an optimized path is generated through B-spline curves. The resulting paths can be optimized with a preference towards maximum safety, minimum fuel consumption or a combination of the two. The problem formulation and solution implementation is described along with the results from several simulated scenarios.
As unmanned units become more capable of self-control, and as their integration into our military forces increase, the role of the operator of these units is going to change. Current UAV ground control systems typical...
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ISBN:
(纸本)1563478234
As unmanned units become more capable of self-control, and as their integration into our military forces increase, the role of the operator of these units is going to change. Current UAV ground control systems typically require to much of the operator's attention per unit, and the role of the future operator will be more like that of a manager than that of a pilot. This paper describes research being done on a user interface for a future ground control system. Beginning with a visualization of a virtual battlefield, this next-generation UAV ground control system incorporates all available information and analyses in combination with a synthetic battlespace in a context-relevant manner. This marriage of synthetic and real information feeds, within a single visualization space, is designed to increase the situational awareness of a single operator. This virtual battlefield provides the operator with the information necessary to accomplish their task, with multiple modes of interaction for the user. The UAV Ground Control System detailed here utilizes a speech command interface, a wireless joystick interface, as well as a tablet-based direct manipulation interface similar to those used in general air unit ground control systems. Through these different types of interactions, an operator is presented with various sources of data to manage and command military units as clearly and simply as possible.
In this paper the authors propose a structural method for a genetic algorithm (GA) for the optimization problem of cable routing in which cables have to be laid optimally. When there are no limits on the layout routes...
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Virtual Probe Microscope (VPM) is a tool that has been developed to train users on Atomic Force Microscope (AFM) operation. The benefits from training with VPM include: reduced cost of training and increased transfer ...
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ISBN:
(纸本)0976798514
Virtual Probe Microscope (VPM) is a tool that has been developed to train users on Atomic Force Microscope (AFM) operation. The benefits from training with VPM include: reduced cost of training and increased transfer of training. The graphical user interface of VPM is laid out similar to common commercial AFM software packages. Along with standard AFM controls, users are given an additional graphical 3D window to view the probe traversing across a surface. Users are also allowed to manipulate probe geometry variable to increase understanding of AFM operation. VPM will be used in a graduate level scanning probe microscopy class in the spring of 2005 at Iowa State University to supplement traditional lab and classroom instruction.
Obtaining local and global planarities is one of the prime criteria in dielectric and metal planarisations. Although chemical mechanical planarisation (CMP) helps us achieve these criteria in constant pattern density ...
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