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Sensor based obstacle avoidance and mapping for fast mobile robots

Sensor based obstacle avoidance and mapping for fast mobile ...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： C. Gourley M. Trivedi Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA

This paper describes one aspect of a project whose goal is to move a robot in an unknown environment and find pipes to decommission. While moving through the environment a low level map, in the form of an occupancy grid, along with detailed location of pipes in the environment are obtained. This paper deals only with the low level "reflex" of obstacle avoidance that is performed while the robot moves along its path as well as some of the higher level tasks involved in path planning and robot motion in order to negotiate through a hazardous environment. The overall high level interaction with the system is made as simple and user friendly as possible using a graphical interface to control high level tasks. All low level communications and processing are transparent. The robot used for experimentation is a wheeled mobile platform equipped with many different sensors including ultrasonic range sensors and cameras. A quick and efficient obstacle avoidance algorithm has been developed using sixteen ultrasonic range sensor and one infrared proximity sensor.< >

关键词： Mobile robots Infrared sensors Robot sensing systems Path planning Robot motion Communication system control Control systems Mobile communication Robot vision systems Cameras

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Simulation and visualization of integrated sensory-motor systems

Simulation and visualization of integrated sensory-motor sys...

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IEEE Workshop on Visualization and Machine vision

作者： S.B. Marapane M.M. Trivedi Computer Vision and Robotics Research Laboratory Department of Electrical and Computer Engineering University of Tennessee Knoxville TN USA

A binocular robot head, BETH, with ten degrees of freedom (DOF) has been developed for research in active vision. To complement BETH, a graphical simulation and visualization environment has also been developed. The objective of building the graphical system is to create a comprehensive design tool to design and study the dynamic behavior of sensory-motor systems and their interactions with the environment. This environment integrates perception and motor actions and features complete kinematic simulation of BETH, it's sensors and it's workspace. We demonstrate the utility of this environment in systematic and extensive experimental development of computational frameworks and algorithms for 3D active vision systems which utilizes multiple passive depth cues (stereo, vergence, and depth from focusing).< >

关键词： Visualization Head Robot sensing systems Robot vision systems computer vision Computational modeling Buildings Focusing Image analysis Machine vision

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Analyzing teams of cooperating mobile robots

Analyzing teams of cooperating mobile robots

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IEEE International Conference on robotics and Automation (ICRA)

作者： B.R. Donald J. Jennings D. Rus Robotics & Vision Laboratory Computer Science Department Cornell University Ithaca NY USA

Donald (1993) described a manipulation task for cooperating mobile robots that can push large, heavy objects. There, the author asked whether explicit local and global communication between the agents can be removed from a family of pushing protocols. In this paper, the authors answer in the affirmative. They do so by using the general methods of Donald for analyzing information invariants. The authors discuss several measures for the information complexity of the task of pushing with cooperating mobile robots, and they present a methodology for creating new manipulation strategies out of existing ones. The authors develop and analyze synchronous and asynchronous manipulation protocols for a small team of cooperating mobile robots than can push large boxes. The protocols described have been implemented in several forms on the Cornell mobile robots in the authors' laboratory.< >

关键词： Mobile robots Robot kinematics Robot sensing systems Protocols Laboratories Information analysis Friction Manipulator dynamics Robot vision systems computer science

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Texture segmentation using circular-Mellin operators

Texture segmentation using circular-Mellin operators

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IEEE International Conference on Image Processing

作者： G. Ravichandran M.M. Trivedi Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA

Texture is an important preattentive cue in region-based segmentation of images. In this paper, we discuss the use of circular-Mellin features for segmenting an image into homogenous regions. The circular-Mellin operators represent the spectral decomposition of the image scene in the polar-log coordinate system and are invariant to both scale and orientation of the target. Coupled with the unique shift invariance property of the correlator architecture, these circular-Mellin operators can be used for rotation- and scale-invariant feature extraction. We note that while both these feature extractors have similar functional form to the Gabor functions, the distortion-invariant characteristics of the circular-Mellin operators make them preferable for texture segmentation. Segmentation results to demonstrate their salient properties are presented.< >

关键词： Image segmentation Layout computer vision Correlators Feature extraction Maximum likelihood detection Filtering theory Gabor filters Nonlinear filters Pattern recognition

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Acquisition of 3D structure of selectable quality from image streams

Acquisition of 3D structure of selectable quality from image...

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IEEE Workshop on Applications of computer vision (WACV)

作者： A.K. Dalmia M. Trivedi Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA

In this paper we present a computational approach for extracting three-dimensional structure of controllable resolution, depth of field, and accuracy, all made available at real-time speeds. This approach utilizes the spatial and the temporal gradients of the streams of images acquired using an actively controlled camera. Depending on the requirements of a particular task, appropriate parameters such as disparity value sought, the inter-frame camera displacement, and number of frames in a stream, are chosen to control the resolution, depth of field, and accuracy. The acquisition and processing of the image stream are done in real-time on a pipeline architecture based processor. Extensive experiments are presented to demonstrate the accuracy, controllability of depth of field and resolution, and ability to perform successfully in a variety of scenes. The system operated with no latency between the image acquisition and processing. The total acquisition and processing time in these experiments is in the range of 0.27 to 1.56 sec. The depth results have an accuracy of 85% to 92%.< >

关键词： Streaming media computer vision Machine vision Cameras Pipelines Spatial resolution Layout Delay Performance analysis Robot vision systems

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Localized Radon transform-based detection of linear features in noisy images

Localized Radon transform-based detection of linear features...

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IEEE computer Society Conference on computer vision and Pattern Recognition Workshops (CVPRW)

作者： Copeland Ravichandran Trivedi Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA

This paper presents a Radon transform-based approach to the detection of linear features in images characterized by high noise levels. This approach is based on the localized Radon transform where the intensity integration is performed over short line segments rather than across the entire image. The algorithm, referred to as the feature space line detector (FSLD) algorithm, is tested on synthetic images of linear features with very high noise levels. The results of this testing demonstrate the algorithm's robustness in the presence of noise, as well as its ability to detect and localize linear features that are significantly shorter than the image dimensions or that display some curvature.< >

关键词： Feature extraction

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Real-time visual tracking using correlation techniques

Real-time visual tracking using correlation techniques

引用

IEEE Workshop on Applications of computer vision (WACV)

作者： M.W. Eklund G. Ravichandran M.M. Trivedi S.B. Marapane Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA

A real-time correspondence based tracking algorithm is detailed. The system uses a pipeline processor, a general purpose processor, a camera and a display. The Minimum Noise and Correlation Energy (MINACE) filter is used in the tracking algorithm as it provides a good combination of speed, accuracy and flexibility for the targeted hardware system. The system designed is fast and tracking is accomplished at a rate of 15 hz. The system is adaptive and does not rely on a previous model of the object; the training image for filter synthesis is acquired from previous image frames and the filter is synthesized online to accommodate 3-D variations of the target being tracked. The system tracks an object consistently as is demonstrated by the low deviation of the results in the evaluation. The correlation filter-based tracking algorithm has proved to be useful in our research in cooperative mobile robots. A visual servoing system has been implemented using this tracking algorithm for convoying of multiple mobile robots.< >

关键词： Target tracking Cameras Robot vision systems Visual servoing computer vision Adaptive filters Mobile robots Laboratories Power engineering and energy Pipelines

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Off-line recognition of signatures using revolving active deformable models

Off-line recognition of signatures using revolving active de...

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IEEE International Conference on Systems, Man and Cybernetics

作者： I. Pavlidis R. Mavuduru N. Papanikolopoulos Artificial Intelligence Robotics and Vision Laboratory Department of Computer Science University of Minnesota Minneapolis MN USA

This paper presents a novel approach to the problem of signature recognition. We introduce the use of revolving active deformable models as a powerful way of capturing the unique characteristics of a signature's silhouette. Experimental evidence shows that the silhouette of a signature uniquely determines the signature in the majority of cases. The objective of our method is to recognize signatures based on the spatial properties of the signature boundaries. Our active deformable models originate from the snakes introduced to computer vision by Kass et al. (1987), but their implementation has been tailored to the task at hand. These computer-generated models interact with the virtual gravity field created by the image gradient. Ideally, the uniqueness of this interaction mirrors the uniqueness of the signature's silhouette. The proposed method obviates the use of a computationally expensive segmentation approach and yields satisfactory results regarding performance, without compromising the accuracy rate. Interestingly, the active deformable models have been implemented in such a way, that the method is potentially fully parallelizable. The experiments performed with a signature database show that the proposed method is promising.< >

关键词： Deformable models Databases Character recognition Handwriting recognition Artificial intelligence Intelligent robots Robot vision systems Laboratories computer science computer vision

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Computation of shape through controlled active exploration

Computation of shape through controlled active exploration

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： C.E. Smith N.P. Papanikolopoulos Artificial Intelligence Robotics and Vision Laboratory Department of Computer Science University of Minnesota Minneapolis MN USA

Accurate knowledge of depth continues to be of critical importance in robotic systems. Without accurate depth knowledge, tasks such as inspection, tracking, grasping, and collision-free motion planning prove to be difficult and often unattainable. Traditional visual depth recovery has relied upon techniques that require the solution of the correspondence problem or require known lighting conditions and Lambertian surfaces. In this paper, we present a technique for the derivation of depth from feature points on a target's surface using the controlled active vision framework. We use a single visual sensor mounted on the end-effector of a robotic manipulator to automatically select feature points and to derive depth estimates for those features using adaptive control techniques. Movements of the manipulator produce displacements that are measured using a sum-of-squared difference (SSD) optical flow. The measured displacements are fed into the controller to alter the path of the manipulator and to refine the depth estimate.< >

关键词： Shape control Manipulators Automatic control Displacement measurement Inspection Tracking Motion planning Sensor phenomena and characterization Robot sensing systems robotics and automation

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Application of the controlled active vision framework to robotic and transportation problems

Application of the controlled active vision framework to rob...

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IEEE Workshop on Applications of computer vision (WACV)

作者： C.E. Smith N.P. Papanikolopoulos S.A. Brandt Artificial Intelligence Robotics and Vision Laboratory Department of Computer Science University of Minnesota Minneapolis MN USA

Flexible operation of a robotic agent in an uncalibrated environment requires the ability to recover unknown or partially known parameters of the workspace through sensing. Of the sensors available to a robotic agent, visual sensors provide information that is richer and more complete than other sensors. In this paper we present robust techniques for the derivation of depth from feature points on a target's surface and for the accurate and high-speed tracking of moving targets. We use these techniques in a system that operates with little or no a priori knowledge of the object-related parameters present in the environment. The system is designed under the controlled active vision framework and robustly determines parameters such as velocity for tracking moving objects and depth maps of objects with unknown depths and surface structure. Such determination of intrinsic environmental parameters is essential for performing higher level tasks such as inspection, exploration, tracking grasping, and collision-free motion planning. For both applications, we use the Minnesota Robotic Visual Tracker (a single visual sensor mounted on the end-effector of a robotic manipulator combined with a real-time vision system) to automatically select feature points on surfaces, to derive an estimate of the environmental parameter in question, and to apply a control vector based upon these estimates to guide the manipulator. The paper concludes with applications of these techniques to transportation problems such as vehicle tracking.< >

关键词： Robot vision systems Robot sensing systems Target tracking Control systems robotics and automation Manipulators Robustness Velocity control Robust control Surface structures

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