D. A. Pomerleau. Neural Network Perception for Mobile Robot Guidance. PhD thesis, Carnegie Mellon University, 1992.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....stochastic source given prior observations. Applying these ideas to the Human Computer Interaction (HCI) domain is called Learning By Observation (LBO) and many similar terms. The best known example of LBO is the neural network system (ALVINN) that learns to drive a car by observing human drivers [7]. In recent years, LBO research has investigated robotic task decomposition [4] nonlinear trajectory emulation [5] and human motion synthesis [6] V. CONCLUSIONS The results from Section III show that a tabula rasa PRP system can predict the waypoints of complex, realworld programs with great ....

D. Pomerleau. Neural Network Perception for Mobile Robot Guidance. PhD thesis, Carnegie Mellon University, 1994.

....Problems such as partial occlusion, changes in illumination, or di#erent postures constantly modify the amount of information of the di#erent visual attributes. As a consequence, the most adequate set of attributes to complete a given task is highly variable. As an example, consider ALVINN [59], a perceptual visual system designed to steer a car in natural environments using a neural net learning algorithm. After training, the main internal features learned by ALVINN were the edges of the road. With this knowledge ALVINN was able to successfully steer a car when the edges of the road ....

D. Pomerleau. Neural Network Perception for Mobile Robot Guidance. Boston: Kluwer Academic Publishers, 1993.

....state based approach to open loop skill learning and telerobotics using Hidden Markov Models (HMMs) Several approaches to skill learning in human driving have been implemented. In [12] neural networks are trained to mimic human be havior for a simulated circu lar racetrack. Pomerleau [13] implements real time road following with data collected from a human driver. A static feedforward neural network, with a single hidden layer, learns to map coarsely digitized camera images of the road ahead to a desired steering direction, whose reliability is given through an ....

D.A. Pomerleau, "Neural Network Perception for Mobile Robot Guidance, " Ph.D. thesis, School of Computer Science, Carnegie Mellon University, 1992.

....substituted inductive learning for conventional program development so that they could train their software to perform non trivial tasks. For example, Pomerleau, in his ALVINN system, trained an artificial neural network to map camera images to steering directions for an autonomous land vehicle [83, 82]. After approximately 10 minutes of training, his system provided a remarkable level of skill in driving on various types of roads and under a wide range of conditions. Coding the same skill manually is difficult, as the work by Dickmanns and his colleagues has shown [23] This example ....

D. Pomerleau. Neural Network Perception for Mobile Robot Guidance. Kluwer Academic Publishers, Boston, MA, 1993.

.... in the 1960s focused on the problem of semi autonomous vehicle control with promising results [15, 25, 4] Significant progress was made when vision based lanetrackers were integrated with vehicle control systems, enabling robot cars to drive on clear highways under controlled circumstances [7, 18, 26]. Simultaneously, research in automatic headway control [3, 6] and convoying [14, 19] led to vehicles capable of autonomous car following [17, 37] In 1995, an intelligent vehicle, the Carnegie Mellon Navlab 5, steered 98 of the distance between Washington D.C. and San Diego (a distance of 2800 ....

D. Pomerleau. Neural Network Perception for Mobile Robot Guidance. PhD thesis, Carnegie Mellon University, February 1992.

....emotions, the system achieved a recognition rate of 86 for mile, 94 for urprise, 92 for anger, 86 for fear, 80 for adness, and 92 for disgust. Blinking detection success rate was 65 . Connectionist architectures have been used in vi sual classification problems with great success [6,3]. The classification of visual imagery, however, has mainly focused on static imagery. Seibert and Wax man [7] recently developed a system that performed object recognition using the object s rigid motion. The neural network learned correlations between different aspect views of an object, and as ....

....chosen represents the stage of an emotion to which an input image of a sequence belongs. The activation of an output unit in this representation corresponds to the network s confidence that the emotion of the current sequence is in the stage corresponding to the particular output unit. Pomerleau [6] found that when there exists a prox imal relation between output units the supervised learning unit activations should reflect this relation. In our application, an output unit represents a stage of an emotion and the stages are related by the obvious temporal proximal relation. If the current ....

D.A. Pomerleau, Neural Network Perception for' Mobile Robot Guidance, Ph.D. thesis, Carnegie Mellon University, Department of Computer Science, 1992.

.... have been deployed in heart disease diagnosis [ Detrano et al. 1989 ] in predicting glucose levels for diabetic patients [ Carson Fischer, 1990 ] in detecting credit card fraud [ Stolfo et al. 1997a ] in steering vehicles driving autonomously on public highways at 70 miles an hour [ Pomerleau, 1992 ] in predicting stock option pricing [ Malliaris Salchenberger, 1993 ] and in computing customized electronic newspapers [ K.Lang, 1995 ] to name a few applications. Many large business institutions and market analysis firms attempt to distinguish the low risk (high profit) potential ....

Pomerleau, D. 1992. Neural network perception for mobile robot guidance. Ph.D. Dissertation, School of Computer Sci., Carnegie Mellon Univ., Pittsburgh, PA. (Tech. Rep. CMU-CS-92-115).

....inputs and human control outputs. Autonomous control and navigation of ground vehicles is one area of robotics research which has benefited from this type of modeling. Pomerleau, for example, has implemented in the ALVINN system real time road following using data collected from a human driver [1,2]. The ALVINN system has learned to map from coarse video images of the road to a desired steering angle and has been demonstrated successfully on public roads at speeds up to 70 mph. Nechyba and Xu have used observation and modeling of human drivers within a driving simulator to successfully ....

.... a message, and prints to disk static int count=0; if( ValidMessage(s1) fprintf(fp, bad1 n ) fprintf(fp,s1) return; if( ValidMessage(s2) fprintf(fp, bad2 n ) fprintf(fp,s2) return; printf( s s n ,s1,s2) HC11 if(sscanf(s2, DATA x, x, x, x , data.servo[0] data.servo[1]) data.servo[2] data.servo[3] EOF) fprintf(fp, bad3 n ) fprintf(fp,s2) return; failed Compass if(sscanf(s1, C fP fR fX fY fZ fT f , data.heading) data.pitch) data.roll) EOF) fprintf(fp, bad4 n ) fprintf(fp,s1) return; failed 44 data.time=tm.time starttm.time; ....

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D.A. Pomerleau, "Neural Network Perception for Mobile Robot Guidance," Ph.D. thesis, Carnegie Mellon University, 1992.

.... in the 1960s focused on the problem of semi autonomous vehicle control with promising results [35, 70, 19] Significant progress was made when visionbased lane trackers were integrated with vehicle control systems, enabling robot cars to drive on clear highways under controlled circumstances [23, 54, 73]. Simultaneously, research in automatic headway control [16, 22] and convoying [34, 55] led to vehicles capable of autonomous car following [52, 101] In 1995, an intelligent vehicle, the Carnegie Mellon Navlab 5, steered 98 of the distance between Wash Throughout this thesis, multiple ....

....characteristics (See Figure 3.2) The intelligent vehicles are designed to be largely compatible with the Carnegie Mellon Navlab [106, 76] robot vehicles (See Figure 3. 3) Over the last decade, the Navlab robots have been used as testbeds for a large variety of experiments in autonomous navigation [61, 73, 101, 104, 74]. Since many of the systems that have emerged from this research will be critical in the automated highway system project, SHIVA minimizes the modifications needed to port cognition modules to the robot. In particular, the interface to the lane trackers and steering speed controller (See Sections ....

[Article contains additional citation context not shown here]

D. Pomerleau. Neural Network Perception for Mobile Robot Guidance. PhD thesis, Carnegie Mellon University, February 1992.

....A number of researchers have worked in recent years to abstract models of human skill directly from observed human input output data . Autonomous control and navigation of ground vehicles is one area of robotics research which has benefited from learning through observation of humans. Pomerleau [3,4], for example, has implemented in the ALVINN system real time road following using data collected from a human driver. A static feedforward neural network with a single hidden layer learned to map from coarsely digitized images of the road ahead to a desired steering angle. The ALVINN system has ....

D.A. Pomerleau, "Neural Network Perception for Mobile Robot Guidance," Ph.D. thesis, Carnegie Mellon University, 1992.

....top left corner ### ## of the screen. Instead of using the commonly seen 1 out of N coding method for representing the desired activation pattern of a gaze point across the two groups of output units, respectively, we have adopted a Gaussian shaped coding method similar to the work by Pomerleau [13] on autonomous vehicle guidance. It is generally agreed that the 1 out of N coding method is more suitable for pattern classification tasks which require sharp definitive decision boundaries between different classes, while the mapping function simulation task of this study demands a gradual ....

D.A. Pomerleau. Neural Network Perception for Mobile Robot Guidance. Kluwer Academic Publishing, 1993.

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D. Pomerleau, Neural Network Perception for Mobile Robot Guidance. PhD thesis, Carnegie Mellon University, February 1992.

....Two other examples of model based reasoning about network performance in the ALVINN system are briefly described. 1. Introduction ALVINN (Autonomous Land Vehicle in a Neural Network) is a neural network based system which has been successful in driving robot vehicles in a variety of situations [1, 2]. However, since ALVINN maintains no state information about the world, but processes each sensor frame individually, it can become confused on sharp curves when the field of view no longer displays the important features in the scene. A steerable sensor allows the perception system to select the ....

Pomerleau, D.A. (1992): Neural Network Perception for Mobile Robot Guidance. Carnegie Mellon technical report CMU-CS-92-115.

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Pomerleau, D.A. (1993) Neural Network Percep- tion Mobile Robot Guidance,Boston: Kluwer Academic Publishing.

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D. A. Pomerleau. Neural Network Perception for Mobile Robot Guidance. PhD thesis, Carnegie Mellon University, 1992.

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Pomerleau, D. A. (1993). Neural Network Perception for Mobile Robot Guidance. Kluwer Academic Publishers, Boston.

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D. Pomerleau. Neural Network Perception for Mobile Robot Guidance. Kluwer Academic Publishers, 1993.

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Pomerleau, D. A.: "Neural network perception for mobile robot guidance" Ph.D. Dissertation, School of Computer Science, Carnegie-Mellon University, Pittsburgh, PA, 1992.

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Pomerleau, D., "Neural Network Perception for Mobile Robot Guidance," Ph.D. thesis, School of Computer Science, Carnegie Mellon University, 1992

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D. Pomerleau. Neural Network Perception for Mobile Robot Guidance. Kluwer Academic Publishers, 1993.

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D.A. Pomerleau. Neural Network Perception for Mobile Robot Guidance. PhD thesis, Carnegie Mellon University, 1992.

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D.A. Pomerleau, Neural Network Perception for Mobile Robot Guidance. Boston, MA: Kluwer Academic Publishers, 1993.

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D. Pomerleau. Neural Network Perception for Mobile Robot Guidance. PhD thesis, Carnegie Mellon University, February 1992.

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Pomerleau, D. A., "Neural Network Perception for Mobile Robot Guidance," Ph.D. Thesis, School of Computer Science, Carnegie Mellon University, 1992.

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D. Pomerleau. Neural Network Perception for Mobile Robot Guidance. PhD thesis, Carnegie Mellon University, February 1992.

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