The intelligent Ground Vehicle Competition (IGVC) is one of three, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI) in the 1990s. The IGVC ...
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ISBN:
(纸本)9780819469243
The intelligent Ground Vehicle Competition (IGVC) is one of three, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI) in the 1990s. The IGVC is a multidisciplinary exercise in product realization that challenges college engineering student teams to integrate advanced control theory, machine vision, vehicular electronics, and mobile platform fundamentals to design and build an unmanned system. Teams from around the world focus on developing a suite of dual-use technologies to equip ground vehicles of the future with intelligent driving capabilities. Over the past 15 years, the competition has challenged undergraduate, graduate and Ph.D. students with real world applications in intelligent transportation systems, the military and manufacturing automation. To date, teams from over 50 universities and colleges have participated. This paper describes some of the applications of the technologies required by this competition and discusses the educational benefits. The primary goal of the IGVC is to advance engineering education in intelligent vehicles and related technologies. The employment and professional networking opportunities created for students and industrial sponsors through a series of technical events over the four-day competition are highlighted. Finally, an assessment of the competition based on participation is presented.
When interacting with intelligent agents, it is vital to understand something of their intentions. Agents' itentions provide context in spoken dialog, help to define their future plans (and thus actions), and reve...
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ISBN:
(纸本)0819426407
When interacting with intelligent agents, it is vital to understand something of their intentions. Agents' itentions provide context in spoken dialog, help to define their future plans (and thus actions), and reveal information about their beliefs. We propose a method by which agents' intentions are inferred by observing their actions. Explicit communication among agents is not permitted. The joint intentions framework(1) specifies the behaviors and obligations of agents that share in a cooperative intention. Our work focuses on the creation of such joint intentions through observation and plan recognition. The plan recognition structure uses Bayes Nets to reason from observations to actions, and Hidden Markov Models to reason from sequences of actions to intent.
This paper describes a method for expressing and manipulating position and orientation uncertainty in sensor-based robotics. The goal is to formulate a computational framework where the effects of accumulating uncerta...
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ISBN:
(纸本)0819426407
This paper describes a method for expressing and manipulating position and orientation uncertainty in sensor-based robotics. The goal is to formulate a computational framework where the effects of accumulating uncertainties, originating from internal and external sensors, are shown as uncertainties in tool frame positions and orientations. The described method is based on using covariance matrices of position and orientation parameters. The used orientation parameters are xyz Euler angles. There are three different forms of spatial uncertainty and uncertainty manipulation involves transformations between these forms. These transformations are done by using linearisation around nominal relations. Paper presents the basic formulas for these transformations and also three calculation examples.
Advanced courses in the areas of Machine Perception and Machine Intelligence are not easy to prepare or conduct due to the dynamic research nature of the field. In engineering, our interest is in the construction of i...
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Advanced courses in the areas of Machine Perception and Machine Intelligence are not easy to prepare or conduct due to the dynamic research nature of the field. In engineering, our interest is in the construction of intelligent machines in the form of robotic devices or through computer simulation models. Studies in this area are further complicated by the broad range of disciplines that must be accessed in order to provide adequate coverage. This discussion focuses on a set of computer simulation projects that have been assigned at various times during offerings of an advanced graduate level course entitled Machine Perception. The format of the projects are presented with discussion of student results. The projects were novel in that they require advanced techniques of machine vision and are open-ended in that there are no specific solutions. The problems represent the mainstream of machine perception research without requiring more effort than is possible in a one semester course. Students responded with algorithms developed in a variety of computer languages and on various machines.
In this paper, a number of spatial/spatial-frequency image representations are reviewed. Wavelets have recently generated much interest, both in applied areas as well as in more theoretical ones. Wavelet tranlorm rela...
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There has been a great interest in the recent years in visual coordination and target tracking for mobile robots cooperating in unstructured environments. This paper describes visual servo control techniques suitable ...
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ISBN:
(纸本)081945155X
There has been a great interest in the recent years in visual coordination and target tracking for mobile robots cooperating in unstructured environments. This paper describes visual servo control techniques suitable for intelligent task planning of cooperative robots operating in unstructured environment. In this paper, we have considered a team of semi-autonomous robots controlled by a remote supervisory control system. We have presented an algorithm for visual position tracking of individual cooperative robots within their working environment. Initially, we present a technique suitable for visual servoing of a robot toward its landmark targets. Secondly, we present an image-processing technique that utilizes images from a remote surveillance camera for localization of the robots within the operational environment. In this algorithm, the surveillance camera can be either stationary or mobile. The supervisor control system keeps tracks of relative locations of individual robots and utilizes relative coordinate information of the robots to plan their cooperative activities. We presented some results of this research effort that illustrates effectiveness of the proposed algorithms for cooperative robotic systems visual team working and target tracking.
The face recognition, one of the most important ability of intelligentvision, are discussed in this paper. A new idea of model-based processing are presented. The algorithms of face modeling, global matching and fine...
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ISBN:
(纸本)0819423068
The face recognition, one of the most important ability of intelligentvision, are discussed in this paper. A new idea of model-based processing are presented. The algorithms of face modeling, global matching and fine matching, and feature points extraction etc. are given Finally, a rapid and robust scheme for human face recognition are resulted.
We advance new active computervisionalgorithms that classify objects and estimate their pose from intensity images. Our algorithms automatically re-position the sensor if the class or pose of an object is ambiguous ...
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ISBN:
(纸本)0819426407
We advance new active computervisionalgorithms that classify objects and estimate their pose from intensity images. Our algorithms automatically re-position the sensor if the class or pose of an object is ambiguous in a given image and incorporate data from multiple object views in determining the final object classification A feature space trajectory (PST) in a global eigenfeature space is used to represent 3-D distorted views of an object. Assuming that an observed feature vector consists of Gaussian noise added to a point on the FST, we derive a probability density function (PDF) for the observation conditioned on the class and pose of the object. Bayesian estimation and hypothesis testing theory are then used to derive approximations to the maximum a posteriori probability pose estimate and the minimum probability of error classifier. New confidence measures for the class and pose estimates: derived using Bayes theory, determine when additional observations are required as well as where the sensor should be positioned to provide the most useful information.
One of the central problems of computervision is segmentation of images into salient features such as edges and surfaces. Different kinds of similarity criteria can be used to group related pixels together. One such ...
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ISBN:
(纸本)0819419524
One of the central problems of computervision is segmentation of images into salient features such as edges and surfaces. Different kinds of similarity criteria can be used to group related pixels together. One such criterion is the curvature of surfaces in an image of a multiobject scene that contains several objects with different shapes. In practice, however, curvature is difficult to calculate because small amount of noise can cause large amounts of errors in calculations of first and second derivatives. In this paper, we use a discrete approximation of Gaussian curvature that is efficient to compute. The approximation is used to segment the image into individual surfaces. Both synthetic and real images have been tested. Results appear quite encouraging.
Stereo vision is attractive for autonomous mobile robot navigation, but the cost and complexity of stereo camera systems and the computational requirements make full stereo vision impractical. A novel optical system a...
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ISBN:
(纸本)9780819469243
Stereo vision is attractive for autonomous mobile robot navigation, but the cost and complexity of stereo camera systems and the computational requirements make full stereo vision impractical. A novel optical system allows the capture of a pair of short, wide stereo images from a single camera, which are then processed to detect vertical edges and infer obstacle positions and locations within the planar field of view, providing real-time obstacle detection. Our optical system involves a pair of right-angle prisms stacked vertically, splitting the camera field of view vertically in half. Right angle mirrors on either side redirect the image forward but at a horizontally displaced location, creating two virtual cameras. Tilting these mirrors provides an overlapping image area. Alternately, tilting the prisms produces the same effect. This image area is wide but not very tall. However, in a mobile robot scenario the majority of obstacles of interest intersect this field of view.
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