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检索条件"任意字段=Conference on Intelligent Robots and Computer Vision XXXII - Algorithms and Techniques"

共 372 条记录，以下是151-160 订阅

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A method for sensor processing, sensor integration, and navigation in mobile autonomous ground vehicles

A method for sensor processing, sensor integration, and navi...

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conference on intelligent robots and computer vision XXIV - algorithms, techniques, and Active vision

作者： Riggins, Robert N. Mutter, Bruce V. Baker, Scott Farmer, Jesse Huntley, Joy Kessler, Joe Lewis, Lenny Bleufield State Coll CART Inc Ctr Appl Res & Technol POB 2182 Bluefield WV 24701 USA

ISBN: (纸本)0819464821

This paper presents an algorithm for solving three challenges of autonomous navigation: sensor signal processing, sensor integration, and path-finding. The algorithm organizes these challenges into three steps. The first step involves converting the raw data from each sensor to a form suitable for real-time processing. Emphasis in the first step is on image processing. In the second step, the processed data from all sensors is integrated into a single map. Using this map as input, during the third step the algorithm calculates a goal and finds a suitable path from robot to the goal. The method presented in this paper completes these steps in this order and the steps repeat indefinitely. The robotic platform designed for testing the algorithm is a six-wheel mid-wheel drive system using differential steering. The robot, called Anassa II, has an electric wheelchair base and a custom-built top and it is designed to participate in the intelligent Ground Vehicle Competition (IGVC). The sensors consist of a laser scanner, a video camera, a Differential Global Positioning System (DGPS) receiver, a digital compass, and two wheel encoders. Since many intelligent vehicles have similar sensors, the approach presented here is general enough for many types of autonomous mobile robots.

关键词： sensor integration autonomous ground robotic vehicles vision path-planning

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Autonomous robot navigation using vision and sensor based algorithm

Autonomous robot navigation using vision and sensor based al...

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conference on intelligent robots and computer vision XXIV - algorithms, techniques, and Active vision

作者： Bhandari, Susmita Mathis, Allison Mohiuddin, Kashif Pietrocola, David Restrepo, Maria Ahlgren, David J. Trinity Coll Dept Engn 300 Summit St Hartford CT 06106 USA

ISBN: (纸本)0819464821

ALVIN-VII is an autonomous vehicle designed to compete in the AUVSI intelligent Ground Vehicle Competition (IGVC). The competition consists of two events, the Autonomous Challenge and Navigation Challenge. Using tri-processor control architecture the information from sonar sensors, cameras, GPS and compass is effectively integrated to map out the path of the robot. In the Autonomous Challenge, the real time data from two Firewire web cameras and an array of four sonar sensors are plotted on a custom-defined polar grid to identify the position of the robot with respect to the obstacles in its path. Depending on the position of the obstacles in the grid, a state number is determined and a command of action is retrieved from the state table. The image processing algorithm comprises a series of steps involving plane extraction, morphological analysis, edge extraction and interpolation, all of which are statistically based allowing optimum operation at varying ambient conditions. In the Navigation Challenge, data from GPS and sonar sensors are integrated on a polar grid with flexible distance thresholds and a state table approach is used to drive the vehicle to the next waypoint while avoiding obstacles. Both algorithms are developed and implemented using National Instruments (NI) hardware and LabVIEW software. The task of collecting and processing information in real time can be time consuming and hence not reactive enough for moving robots. Using three controllers, the image processing is done separately for each camera while a third controller integrates the data received through an Ethernet connection.

关键词： autonomous robot image processing navigation sensors algorithm

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Obstacle recognition using region-based color segmentation techniques for mobile robot navigation

Obstacle recognition using region-based color segmentation t...

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conference on intelligent robots and computer vision XXIV - algorithms, techniques, and Active vision

作者： McKeon, Robert T. Krishnan, Mohan Paulik, Mark Univ Detroit Mercy Dept Elect & Comp Engn Detroit MI 48221 USA

ISBN: (纸本)0819464821

This work has been performed in conjunction with the ECE Department's autonomous vehicle entry in the 2006 intelligent Ground Vehicle Competition (***). The course to be traversed in the competition consists of a lane demarcated by paint lines on grass along with other challenging artifacts such as a sandpit, a ramp, potholes, colored tarps, and obstacles set up using orange and white construction barrels. In this paper an enhanced obstacle detection and mapping algorithm based on region-based color segmentation techniques is described. The main purpose of this algorithm is to detect obstacles which are not properly identified by the LADAR (Laser Detection and Ranging) system optimally mounted close to the ground, due to "shadowing" occasionally resulting in bad navigation decisions. On the other hand, the camera that is primarily used to detect the lane lines is mounted at 6 feet. In this work we concentrate on the identification of orange/red construction barrels. This paper proposes a generalized color segmentation technique which is potentially more versatile and faster than traditional full or partial color segmentation approaches. The developed algorithm identifies the shadowed items within the camera's field of vision and uses this to complement the LADAR information, thus facilitating an enhanced navigation strategy. The identification of barrels also aids in deleting bright objects from images which contain lane lines, which improves lane line identification.

关键词： image color analysis image processing image segmentation object recognition

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Obstacle avoidance using predictive vision based on a dynamic 3D world model

Obstacle avoidance using predictive vision based on a dynami...

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conference on intelligent robots and computer vision XXIV - algorithms, techniques, and Active vision

作者： Benjamin, D. Paul Lyons, Damian Achtemichuk, Tom Pace Univ Dept Comp Sci 1 Pace Pl New York NY 10038 USA Fordham Univ Dept Comp & Informat Sci Bronx NY 10458 USA

ISBN: (纸本)0819464821

We have designed and implemented a fast predictive vision system for a mobile robot based on the principles of active vision. This vision system is part of a larger project to design a comprehensive cognitive architecture for mobile robotics. The vision system represents the robot's environment with a dynamic 3D world model based on a 3D gaming platform (Ogre3D). This world model contains a virtual copy of the robot and its environment, and outputs graphics showing what the virtual robot "sees" in the virtual world;this is what the real robot expects to see in the real world. The vision system compares this output in real time with the visual data. Any large discrepancies are flagged and sent to the robot's cognitive system, which constructs a plan for focusing on the discrepancies and resolving them, e.g. by updating the position of an object or by recognizing a new object. An object is recognized only once;thereafter its observed data are monitored for consistency with the predictions, greatly reducing the cost of scene understanding. We describe the implementation of this vision system and how the robot uses it to locate and avoid obstacles.

关键词： mobile robotics active vision cognitive architecture predictive vision

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Moving target detection through omniorientational vision fixed on AGV

Moving target detection through omniorientational vision fix...

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conference on intelligent robots and computer vision XXIV - algorithms, techniques, and Active vision

作者： Yang Shu-Ying Cao Zuo-Liang He Pei-Lian Tianjin Univ Tianjin 300072 Peoples R China Tianjin Univ Technol Tianjin 300191 Peoples R China

ISBN: (纸本)0819464821

Extremely wide view of the onmi-vision performs highly advanced for the vehicle navigation and target detection. However moving targets detection through omni-vision fixed on AGV (Automatic Guided Vehicle) involves more complex environments, where both the targets and the vehicle are in the moving condition. The moving targets will be detected in a moving background. After analyzing the character on orriniorientational vision and image, we propose to use the estimation in optical flow fields, Gabor filter over optical flow fields for detecting moving objects. Because polar angle theta and polar radius R of polar coordinates are being changed as the targets moving, we improved optical flow approach which can be calculated based on the polar coordinates at the oniniorientational center. We constructed Gabor filter which has 24 orientations every 15', and filter optical flow fields at 24 orientations. By the contrast of the Gabor filter images at the same orientation and the same AGV position between the situation which there aren't any moving targets in the environment and the situation which there are some moving targets in the same environment, the moving targets' optical flow fields could be recognized. Experiment results show that the proposed approach is feasible and effective.

关键词： optical flow omniorientational vision Gabor filters

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Embodying a cognitive model in a mobile robot

Embodying a cognitive model in a mobile robot

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conference on intelligent robots and computer vision XXIV - algorithms, techniques, and Active vision

作者： Benjamin, D. Paul Lyons, Damian Lonsdale, Deryle Pace Univ Dept Comp Sci 1 Pace Plaza New York NY 10038 USA Fordham Univ Dept Comp & Informat Sci Bronx NY 10458 USA Brigham Young Univ Dept Linguist & English Language Provo UT 84602 USA

ISBN: (纸本)0819464821

The ADAPT project is a collaboration of researchers in robotics, linguistics and artificial intelligence at three universities to create a cognitive architecture specifically designed to be embodied in a mobile robot. There are major respects in which existing cognitive architectures are inadequate for robot cognition. In particular, they lack support for true concurrency and for active perception. ADAPT addresses these deficiencies by modeling the world as a network of concurrent schemas, and modeling perception as problem solving. Schemas are represented using the RS (Robot Schemas) language, and are activated by spreading activation. RS provides a powerful language for distributed control of concurrent processes. Also, The formal semantics of RS provides the basis for the semantics of ADAPT's use of natural language. We have implemented the RS language in Soar, a mature cognitive architecture originally developed at CMU and used at a number of universities and companies. Soar's subgoaling and learning capabilities enable ADAPT to manage the complexity of its environment and to learn new schemas from experience. We describe the issues faced in developing an embodied cognitive architecture, and our implementation choices.

关键词： mobile robotics cognitive architecture predictive vision learning robot schemas ADAPT

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Lane identification and path planning for autonomous mobile robots

Lane identification and path planning for autonomous mobile ...

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conference on intelligent robots and computer vision XXIV - algorithms, techniques, and Active vision

作者： McKeon, Robert T. Paulik, Mark Krishnan, Mohan Univ Detroit Mercy Dept Elect & Comp Engn Detroit MI 48221 USA

ISBN: (纸本)0819464821

This work has been performed in conjunction with the University of Detroit Mercy's (UDM) ECE Department autonomous vehicle entry in the 2006 intelligent Ground Vehicle Competition (***. The IGVC challenges engineering students to design autonomous vehicles and compete in a variety of unmanned mobility competitions. The course to be traversed in the competition consists of a lane demarcated by painted lines on grass with the possibility of one of the two lines being deliberately left out over segments of the course. The course also consists of other challenging artifacts such as sandpits, ramps, potholes, and colored tarps that alter the color composition of scenes, and obstacles set up using orange and white construction barrels. This paper describes a composite lane edge detection approach that uses three algorithms to implement noise filters enabling increased removal of noise prior to the application of image thresholding. The first algorithm uses a row-adaptive statistical filter to establish an intensity floor followed by a global threshold based on a reverse cumulative intensity histogram and a priori knowledge about lane thickness and separation. The second method first improves the contrast of the image by implementing an arithmetic combination of the blue plane (RGB format) and a modified saturation plane (HSI format). A global threshold is then applied based on the mean of the intensity image and a user-defined offset. The third method applies the horizontal component of the Sobel mask to a modified gray scale of the image, followed by a thresholding method similar to the one used in the second method. The Hough transform is applied to each of the resulting binary images to select the most probable line candidates. Finally, a heuristics-based confidence interval is determined, and the results sent on to a separate fuzzy polar-based navigation algorithm, which fuses the image data with that produced by a laser scanner (for obstacle detection).

关键词： image processing image filtering thresholding path planning autonomous navigation

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Heterogeneous Multi-Robot Localization in Unknown 3D Space

Heterogeneous Multi-Robot Localization in Unknown 3D Space

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2006 IEEE/RSJ International conference on intelligent robots and Systems

作者： Yi Feng Zhigang Zhu Jizhong Xiao Department of Computer Science CUNY NY USA Department of Computer Science City College of New York NY USA

This paper presents a self-localization strategy for a team of heterogeneous mobile robots including ground mobile robots of various sizes and wall-climbing robots. These robots are equipped with various visual sensors, such as miniature webcams, omnidirectional cameras, and PTZ cameras. As the core of this work, a formation of four-robot team is constructed to operate in a 3D space, e.g., moving on ground, climbing on walls and clinging to ceilings. The four robots could dynamically localize themselves asynchronously by employing cooperative vision techniques. Three of them on the ground mutually view each other and determine their relative poses with 6 degrees of freedom (DOFs). A wall-climbing robot, which significantly extends the work space of the robot team to 3D, is at a vantage point (e.g., on the ceiling) such that it can see all the three teammates, thus determining its own location and orientation. The four-robot formation theory and algorithms are presented, and experimental results with both simulated and real image data are provided to demonstrate the feasibility of this formation. Two 3D localization and control strategies are designed for applications such as search and rescue and surveillance in 3D urban environments where robots must be deployed in a full 3D space

关键词： Orbital robotics Robot kinematics Mobile robots Robot sensing systems Robot vision systems Cameras Service robots intelligent robots computer science Cities and towns

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A Delay-tolerant, Potential field-based, Network Implementation of an Integrated Navigation System

A Delay-tolerant, Potential field-based, Network Implementat...

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2006 IEEE/RSJ International conference on intelligent robots and Systems

作者： Rachana Ashok Gupta Ahmad A Masoud Mo-yuen Chow Electrical and Computer Engineering Department North Carolina State University Raleigh NC USA Lectrical Engineering Department KFUPM Dhahran Saudi Arabia Electrical Engineering Department KFUPM Dhahran Saudi Arabia

intelligent space (iSpace) is a large scale mechatronics system. It is a multidisciplinary effort whose aim is to produce a network structure and components that are capable of integrating sensors, actuators, DSP, communication, and control algorithms in a manner that suits time-sensitive applications including real-time navigation and/or obstacle avoidance. There are many challenges that must be overcome in order to put such a distributed, heterogeneous system together. This paper deals with one of these issues, i.e. the adverse effect of network and processing delays on the system. Here a delay-resistant sensory motor module for navigating a differential drive unmanned ground vehicle (UGV) in a cluttered environment is suggested. The module consists of an early vision edge detection stage, a harmonic potential field (HPF) planner, a network based quadratic curve fitting controller and gain schedule middleware, (GSM). Though the different techniques used to implement the navigation system have been well-studied as independent modules, the contribution in this paper is the way all these different modules are integrated together for the first time to create an efficient structure for a network based integrated navigation system. The structure of this module and its components are described. Thorough experimental results along with performance assessment comparing the suggested structure to a previous implementation of iSpace are also provided

关键词： Navigation intelligent sensors Delay systems intelligent systems intelligent actuators Large-scale systems Mechatronics Digital signal processing Communication system control Delay effects

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Stereo Analysis Extension Based on BRDF Reciprocity

Stereo Analysis Extension Based on BRDF Reciprocity

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International conference on Electronics, Communications and computers (CONIELECOMP)

作者： A. Morales-Reyes M. Arias-Estrada Optics and Electronics Computer Science Department National Institute for Astrophysics Optics and Electronics Tonantzintla Puebla Mexico

This paper presents an extension of the binocular technique which considers reciprocal reflectance of surfaces. This particular property allows to recover depth information for surfaces where others stereo techniques failed, for example, textureless and highly specular surfaces. The consideration of an arbitrary BRDF (Bidirectional Reflectance Distribution Function) improves conventional stereo algorithms, in such a way that explicit or implicit assumptions about a reflectance function are not necessary and dense depth maps are obtained. Fixed specularities and correspondence between half-occluded regions reduce processing complexity which is an important advantage of this methodology. This paper provides a general geometry assembly to this approach extending its applicability to some specific areas where accurate depth measures are required. Several results from our implementation are shown using rendered ray-tracing stereo images.

关键词： Reflectivity Surface texture Stereo vision Lighting Rendering (computer graphics) Ray tracing intelligent robots Quality control Biomedical imaging Layout

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