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

共 373 条记录，以下是11-20 订阅

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The 19TH Annual intelligent Ground Vehicle Competition: Student Built Autonomous Ground Vehicles

The 19TH Annual Intelligent Ground Vehicle Competition: Stud...

引用

conference on intelligent robots and computer vision xxix - algorithms and techniques

作者： Theisen, Bernard L. USA TARDEC Warren MI 48397 USA

ISBN: (纸本)9780819489487

The intelligent Ground Vehicle Competition (IGVC) is one of four, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI). 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 19 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 almost 80 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.

关键词： intelligent robots autonomous systems ground vehicles vehicle control engineering education IGVC

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The Magic Glove: A Gesture-Based Remote Controller for intelligent Mobile robots

The Magic Glove: A Gesture-Based Remote Controller for Intel...

引用

conference on intelligent robots and computer vision xxix - algorithms and techniques

作者： Luo, Chaomin Chen, Yue Krishnan, Mohan Paulik, Mark Univ Detroit Mercy Dept Elect & Comp Engn Detroit MI 48221 USA

ISBN: (纸本)9780819489487

This paper describes the design of a gesture-based Human Robot Interface (HRI) for an autonomous mobile robot entered in the 2010 intelligent Ground Vehicle Competition (IGVC). While the robot is meant to operate autonomously in the various Challenges of the competition, an HRI is useful in moving the robot to the starting position and after run termination. In this paper, a user-friendly gesture-based embedded system called the Magic Glove is developed for remote control of a robot. The system consists of a microcontroller and sensors that is worn by the operator as a glove and is capable of recognizing hand signals. These are then transmitted through wireless communication to the robot. The design of the Magic Glove included contributions on two fronts: hardware configuration and algorithm development. A triple axis accelerometer used to detect hand orientation passes the information to a microcontroller, which interprets the corresponding vehicle control command. A Bluetooth device interfaced to the microcontroller then transmits the information to the vehicle, which acts accordingly. The user-friendly Magic Glove was successfully demonstrated first in a Player/Stage simulation environment. The gesture-based functionality was then also successfully verified on an actual robot and demonstrated to judges at the 2010 IGVC.

关键词： Magic Glove gesture-based remote controller Player/Stage accelerometer microcontroller Bluetooth device intelligent mobile robots

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A modular real-time vision module for humanoid robots

A modular real-time vision module for humanoid robots

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conference on intelligent robots and computer vision xxix - algorithms and techniques

作者： Trifan, Alina Neves, Antonio J. R. Lau, Nuno Cunha, Bernardo Univ Aveiro IEETA DETI P-3810193 Aveiro Portugal

ISBN: (纸本)9780819489487

Robotic vision is nowadays one of the most challenging branches of robotics. In the case of a humanoid robot, a robust vision system has to provide an accurate representation of the surrounding world and to cope with all the constraints imposed by the hardware architecture and the locomotion of the robot. Usually humanoid robots have low computational capabilities that limit the complexity of the developed algorithms. Moreover, their vision system should perform in real time, therefore a compromise between complexity and processing times has to be found. This paper presents a reliable implementation of a modular vision system for a humanoid robot to be used in color-coded environments. From image acquisition, to camera calibration and object detection, the system that we propose integrates all the functionalities needed for a humanoid robot to accurately perform given tasks in color-coded environments. The main contributions of this paper are the implementation details that allow the use of the vision system in real-time, even with low processing capabilities, the innovative self-calibration algorithm for the most important parameters of the camera and its modularity that allows its use with different robotic platforms. Experimental results have been obtained with a NAO robot produced by Aldebaran, which is currently the robotic platform used in the RoboCup Standard Platform League, as well as with a humanoid build using the Bioloid Expert Kit from Robotis. As practical examples, our vision system can be efficiently used in real time for the detection of the objects of interest for a soccer playing robot (ball, field lines and goals) as well as for navigating through a maze with the help of color-coded clues. In the worst case scenario, all the objects of interest in a soccer game, using a NAO robot, with a single core 500Mhz processor, are detected in less than 30ms. Our vision system also includes an algorithm for self-calibration of the camera parameters as well

关键词： Robotics robotic soccer computer vision object recognition humanoid robots color classification

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Method for fast detecting the intersection of a plane and a cube in an octree structure to find point sets within a convex region

Method for fast detecting the intersection of a plane and a ...

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conference on intelligent robots and computer vision xxix - algorithms and techniques

作者： Fujimoto, K. Kimura, N. Moriya, T. Hitachi Ltd Cent Res Lab Tokyo 1828601 Japan

ISBN: (纸本)9780819489487

Performing efficient view frustum culling is a fundamental problem in computer graphics. In general, an octree is used for view frustum culling. The culling checks the intersection of each octree node (cube) against the planes of the view frustum. However, this involves many calculations. We propose a method for fast detecting the intersection of a plane and a cube in an octree structure. When we check which child of the octree node intersects a plane, we compare the coordinates of the corner of the node and the plane. Using an octree, we calculate the vertices of the child node by using the vertices of the parent node. To find points within a convex region, a visibility test is performed by AND operation with the result of three or more planes. In experiments, we tested the problem of searching for the visible point with a camera. The method was two times faster than the conventional method, which detects a visible octree node by using the inner product of the plane and each corner of the node.

关键词： Octree View frustum culling computer graphics Point rendering

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Navigating with VFH: A Strategy to Avoid Traps

Navigating with VFH: A Strategy to Avoid Traps

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conference on intelligent robots and computer vision xxix - algorithms and techniques

作者： Luo, Chaomin Krishnan, Mohan Paulik, Mark Mohammad, Utayba Wang, Qing Univ Detroit Mercy Dept Elect & Comp Engn Detroit MI 48221 USA

ISBN: (纸本)9780819489487

The IGVC Navigation Challenge course configuration has evolved in complexity to a point where use of a simple reactive local navigation algorithm presents problems in course completion. A commonly used local navigation algorithm, the Vector Field Histogram (VFH), is relatively fast and thus suitable when computational capabilities on a robot are limited. One of the attendant disadvantages of this algorithm is that a robot can get trapped when attempting to get past a concave obstacle structure. The Navigation Challenge course now has several such structures, including some that partially surround waypoints. Elaborate heuristics are needed to make VFH viable in such a situation and their tuning is arduous. An alternate approach that avoids the use of heuristics is to combine a dynamic path planning algorithm with VFH. In this work, the D*Lite path planning algorithm is used to provide VFH with intermediate goals, which the latter then uses as stepping stones to its final destination. Results from simulation studies as well as field deployment are used to illustrate the benefits of using the local navigator in conjunction with a path planner.

关键词： D*Lite Vector Field Histogram (VFH) path planning Navigation Challenge breadcrumbs intelligent mobile robots

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An approach to stereo-point cloud registration using image homographies

An approach to stereo-point cloud registration using image h...

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conference on intelligent robots and computer vision xxix - algorithms and techniques

作者： Fox, Stephen D. Lyons, Damian M. Fordham Univ Robot & Comp Vis Lab Bronx NY 10458 USA

ISBN: (纸本)9780819489487

A mobile robot equipped with a stereo camera can measure both the video image of a scene and the visual disparity in the scene. The disparity image can be used to generate a collection of points, each representing the location of a surface in the visual scene as a 3D point with respect to the location of the stereo camera: a point cloud. If the stereo camera is moving, e. g., mounted on a moving robot, aligning these scans becomes a difficult, and computationally expensive problem. Many finely tuned versions of the iterative closest point algorithm (ICP) have been used throughout robotics for registration of these sets of scans. However, ICP relies on theoretical convergence to the nearest local minimum of the dynamical system: there is no guarantee that ICP will accurately align the scans. In order to address two problems with ICP, convergence time and accuracy of convergence, we have developed an improvement by using salient keypoints from successive video images to calculate an affine transformation estimate of the camera location. This transformation, when applied to the target point cloud, provides ICP an initial guess to reduce the computational time required for point cloud registration and improve the quality of registration. We report ICP convergence times with and without image information for a set of stereo data point clouds to demonstrate the effectiveness of the approach.

关键词： registration point cloud alignment scan-matching iterative closest point mobile robot stereo vision computer vision homography egomotion

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Decentralized tracking of humans using a camera network

Decentralized tracking of humans using a camera network

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conference on intelligent robots and computer vision xxix - algorithms and techniques

作者： Gruenwedel, Sebastian Jelaca, Vedran Nino-Castaneda, Jorge Oswaldo Van Hese, Peter Van Cauwelaert, Dimitri Veelaert, Peter Philips, Wilfried Ghent Univ TELIN IPI IBBT B-9000 Ghent Belgium

ISBN: (纸本)9780819489487

Real-time tracking of people has many applications in computer vision and typically requires multiple cameras;for instance for surveillance, domotics, elderly-care and video conferencing. However, this problem is very challenging because of the need to deal with frequent occlusions and environmental changes. Another challenge is to develop solutions which scale well with the size of the camera network. Such solutions need to carefully restrict overall communication in the network and often involve distributed processing. In this paper we present a distributed person tracker, addressing the aforementioned issues. Real-time processing is achieved by distributing tasks between the cameras and a fusion node. The latter fuses only high level data based on low-bandwidth input streams from the cameras. This is achieved by performing tracking first on the image plane of each camera followed by sending only metadata to a local fusion node. We designed the proposed system with respect to a low communication load and towards robustness of the system. We evaluate the performance of the tracker in meeting scenarios where persons are often occluded by other persons and/or furniture. We present experimental results which show that our tracking approach is accurate even in cases of severe occlusions in some of the views.

关键词： computer vision decentralized architecture sensor fusion target tracking multi-camera tracking occupancy mapping

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Radial Polar Histogram: obstacle avoidance and path planning for robotic cognition and motion control

Radial Polar Histogram: obstacle avoidance and path planning...

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conference on intelligent robots and computer vision xxix - algorithms and techniques

作者： Wang, Po-Jen Keyawa, Nicholas R. Euler, Craig Calif State Univ Northridge Northridge CA 91330 USA

ISBN: (纸本)9780819489487

In order to achieve highly accurate motion control and path planning for a mobile robot, an obstacle avoidance algorithm that provided a desired instantaneous turning radius and velocity was generated. This type of obstacle avoidance algorithm, which has been implemented in California State University Northridge's intelligent Ground Vehicle (IGV), is known as Radial Polar Histogram (RPH). The RPH algorithm utilizes raw data in the form of a polar histogram that is read from a Laser Range Finder (LRF) and a camera. A desired open block is determined from the raw data utilizing a navigational heading and an elliptical approximation. The left and right most radii are determined from the calculated edges of the open block and provide the range of possible radial paths the IGV can travel through. In addition, the calculated obstacle edge positions allow the IGV to recognize complex obstacle arrangements and to slow down accordingly. A radial path optimization function calculates the best radial path between the left and right most radii and is sent to motion control for speed determination. Overall, the RPH algorithm allows the IGV to autonomously travel at average speeds of 3mph while avoiding all obstacles, with a processing time of approximately 10ms.

关键词： Robotics intelligent ground vehicle cognition motion control path planning obstacle avoidance

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A real time vehicles tracking system for an outdoor mobile robot

A real time vehicles tracking system for an outdoor mobile r...

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

作者： Ge, Kanbing Forging Ctr Co Ltd Osaka Japan

This paper describes progress toward a street-crossing system for an outdoor mobile robot. The system can detect and track vehicles in real time. It reasons about extracted motion regions to decide when it is safe to ... 详细信息

ISBN: (纸本)9780819469243

关键词： mobile robots street crossing computer vision vehicle tracking

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Dynamic vision systems for intelligent robots

Dynamic vision systems for intelligent robots

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conference on intelligent robots and computer vision XX: algorithms, techniques, and Active vision

作者： Nguyen, MC Bui, DT TUM Dept Comp Sci Munich Germany

ISBN: (纸本)081944300X

The logical structure of robot vision systems is introduced. It can be used as a basis for designing such systems. Both sensor data fusion and knowledge representation in a vision system may be broken down into four hierarchical levels where at each level knowledge representation in the form of partial models and data fusion complement each other. Multi-processor architectures supporting this type of structure are introduced as a particularly efficient basis for robot vision systems. Practical implementation is given.

关键词： dynamic vision systems intelligent robots robot vision

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