In this paper, hardware integration and control design for a dual-axis linear stepper (Sawyer) motor are addressed. In particular, the Sawyer motor used in the Yaskawa/MotoMan manufacturing system which is utilized in...
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In this paper, hardware integration and control design for a dual-axis linear stepper (Sawyer) motor are addressed. In particular, the Sawyer motor used in the Yaskawa/MotoMan manufacturing system which is utilized in various applications such as assembly, packaging, sorting, and probing, is considered. These motors are equipped with four optical sensors with a position resolution of 0.25 microns. We develop a detailed model of the motor for control validation and provide a comparison of two control designs, namely, a PD (or PID) and a robust adaptive nonlinear controller. To achieve high performance, a number of practical issues (such as delay/latency, finite sampling time, sensor noise, commutation rate, etc.) need to be considered. Effects of these factors are outlined and experimentally demonstrated. Both the considered controllers utilize knowledge of motor position and velocity in all axes. Current measurements are not required. Either numerical differentiation or a dynamic observer can be used to construct the velocity signals from the measured position data. The designed nonlinear controller provides practical stabilization of position tracking errors and achieves better overall performance. Adaptations are utilized so that no knowledge of the electromechanical system parameters is required. The proposed nonlinear controller is robust to load torques, friction, cogging forces, and other disturbances satisfying certain bounds. Furthermore, the controller corrects for the unintended yaw and achieves synchrony of the motor and rotor teeth. We have also observed that if the rotational motion is not corrected for, the performance is very poor for both controllers. This is also true in the case of delay/latency and higher rates of commutation.
The image sequence of a static scene includes similar or redundant information over time. Hence, motion-discontinuous instants can efficiently characterize a video shot or event. However, such instants (key frames) ar...
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The image sequence of a static scene includes similar or redundant information over time. Hence, motion-discontinuous instants can efficiently characterize a video shot or event. However, such instants (key frames) are differently identified according to the change of velocity and acceleration of motion, and such scales of change might be different on each sequence of the same event. In this paper, we present a scalable video abstraction in which the key frames are obtained by the maximum curvature of camera motion at each temporal scale. The scalability means dealing with the velocity and acceleration change of motion. In the temporal neighborhood determined by the scale, the scene features (motion, color, and edge) can be used to index and classify the video events. Therefore, those key frames provide temporal interest points (TIPs) for the abstraction and classification of video events.
Transference of controllers evolved in simulation to real vehicles is an important issue in evolutionary robotics (ER). We have previously evolved autonomous navigation controllers for fixed wing UAV applications usin...
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Transference of controllers evolved in simulation to real vehicles is an important issue in evolutionary robotics (ER). We have previously evolved autonomous navigation controllers for fixed wing UAV applications using multi-objective genetic programming (GP). Controllers were evolved to locate a radar source, navigate the UAV to the source efficiently using on-board sensor measurements, and circle around the emitter. We successfully tested an evolved UAV controller on a wheeled mobile robot. A passive sonar system on the robot was used in place of the radar sensor, and a speaker emitting a tone was used as the target in place of a radar. Using the evolved navigation controller, the mobile robot moved to the speaker and circled around it. The results from this experiment demonstrate that our evolved controllers are capable of transference to real vehicles. Future research will include testing the best evolved controllers by using them to fly real UAVs.
The U.S. Army Night vision and Electronic Sensors Directorate and the U.S. Army researchlaboratory have developed a terahertz-band imaging system performance model for detection and identification of concealed weapon...
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The U.S. Army Night vision and Electronic Sensors Directorate and the U.S. Army researchlaboratory have developed a terahertz-band imaging system performance model for detection and identification of concealed weaponry. The MATLAB-based model accounts for the effects of all critical sensor and display components, and for the effects of atmospheric attenuation, concealment material attenuation, and active illumination. The model is based on recent U.S. Army NVESD sensor performance models that couple system design parameters to observer-sensor field performance using the acquire methodology for weapon identification performance predictions. This THz model has been developed in support of the Defense Advanced research Project Agencies' Terahertz Imaging Focal-Plane-Array Technology (TIFT) program and is presently being used to guide the design and development of a 0.650 THz active/passive imaging system. This paper will describe the THz model in detail, provide and discuss initial modeling results for a prototype THz imaging system, and outline plans to validate and calibrate the model through human perception testing.
This paper presents the development of the modeling strategy of the human driving behavior based on the expression as Piecewise Linear (PWL) model focusing on the driver’s stopping maneuver. The driving data are coll...
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This paper presents the development of the modeling strategy of the human driving behavior based on the expression as Piecewise Linear (PWL) model focusing on the driver’s stopping maneuver. The driving data are collected by using the three-dimensional driving simulator based on CAVE, which provides stereoscopic immersive vision. In our modeling, the relationship between the driver’s sensory information and the operation of the driver such as braking amount is expressed by PWL model, which is a class of Hybrid Dynamical System (HDS). The identification problem for the PWL model is formulated as the Mixed Integer Linear Programming (MILP) by transforming the switching conditions into binary variables. From the obtained results, it is found that the driver appropriately switches the ‘control low’ according to the sensory information. These results enable us to capture not only the physical meaning of the driving skill, but also the decision-making aspect (switching conditions) in the driver’s stopping maneuver.
This paper introduces a fully automated dimensional inspection (ADI) system using a digital area sensor. Instead of measuring a part surface point-by-point using a Coordinate Measuring Machine (CMM), an ADI system can...
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This paper introduces a fully automated dimensional inspection (ADI) system using a digital area sensor. Instead of measuring a part surface point-by-point using a Coordinate Measuring Machine (CMM), an ADI system can measure a part surface patch-by-patch. Therefore, the inspection time can be significantly reduced. Many existing sensor planners were developed for one or two cameras. In the proposed ADI system, the sensor planner is developed for a digital area sensor, which is made by a CCD camera and a digital projector. In application, sensor viewpoints are estimated automatically. On each viewpoint, thousands of points on part surfaces can be measured in only several seconds.
We have developed several millimeter/submillimeter/terahertz systems to study active and passive imaging and associated phenomenology. For measuring the transmission and scattering properties of materials, we have dev...
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We have developed several millimeter/submillimeter/terahertz systems to study active and passive imaging and associated phenomenology. For measuring the transmission and scattering properties of materials, we have developed a dual rotary stage scattering system with active illumination and a Fourier Transform spectrometer. For imaging studies, we have developed a system based on a 12-inch diameter raster-scanned mirror. By interchange of active sources and both heterodyne and bolometric detectors, this system can be used in a variety of active and passive configurations. The laboratory measurements are used as inputs for, and model calibration and validation of, a terahertz imaging system performance model used to evaluate different imaging modalities for concealed weapon identification. In this paper, we will present examples of transmission and scattering measurements for common clothing as well as active imaging results that used a 640 GHz source and receiver.
This paper reports on methods and technical equipment to investigate the epiretinal stimulation of the retina in blind human subjects in acute trials. Current is applied to the retina through a thin, flexible microcon...
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This paper presents a system that tracks human heads in real-time under unconstrained environments where target occlusion, varying illumination, and cluttered backgrounds exist. Tracking is formulated as an active vis...
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In this paper we discuss the very important issue of indoor location services. Location services have been in use, and studied, for a long time in mobile networks. With the proliferation of wireless networking technol...
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In this paper we discuss the very important issue of indoor location services. Location services have been in use, and studied, for a long time in mobile networks. With the proliferation of wireless networking technologies, users are mostly interested in advanced services that render the surrounding environment (i.e., the building) highly intelligent and significantly facilitate user activities (pervasive computing paradigm). Our focus is on navigation, one of the most important location services. Existing approaches for indoor navigation are driven by geometric information and neglect important aspects like the semantics of points/areas and user preferences. The derived applications are not intelligent enough to catalytically contribute to the pervasive computing vision. In this paper, a novel navigation mechanism is introduced. Such navigation scheme is enriched with user profiles and the adoption of an ontological framework. These enhancements introduce a series of technical challenges that are extensively discussed throughout the paper.
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