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检索条件"任意字段=Intelligent Robots and Computer Vision XXVIII: Algorithms and Techniques"

共 689 条记录，以下是101-110 订阅

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Design and Realization of an intelligent Ground Vehicle with Modular Payloads

Design and Realization of an Intelligent Ground Vehicle with...

引用

Conference on intelligent robots and computer vision XXIX - algorithms and techniques

作者： Akmanalp, Mehmet A. Doherty, Ryan M. Gorges, Jeffrey Kalauskas, Peter Peterson, Ellen Polido, Felipe Nestinger, Stephen S. Padir, Taskin Worcester Polytech Inst Robot Engn Program Worcester MA 01609 USA

ISBN: (纸本)9780819489487

In June 2011, Worcester Polytechnic Institute's (WPI) unmanned ground vehicle Prometheus participated in the 8th Annual Robotic Lawnmower and 19th Annual intelligent Ground Vehicle Competitions back-to-back. This paper details the two-year design and development cycle for WPI's intelligent ground vehicle, Prometheus. The on-board intelligence algorithms include lane detection, obstacle avoidance, path planning, world representation and waypoint navigation. The authors present experimental results and discuss practical implementations of the intelligence algorithms used on the robot.

关键词： Autonomous ground vehicle modular payloads path planning

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Hierarchical Loop Detection for Mobile Outdoor robots

Hierarchical Loop Detection for Mobile Outdoor Robots

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Conference on intelligent robots and computer vision XXIX - algorithms and techniques

作者： Lang, Dagmar Winkens, Christian Haeselich, Marcel Paulus, Dietrich Univ Koblenz Landau AGAS Robot Act Vis Grp D-56070 Koblenz Germany

ISBN: (纸本)9780819489487

Loop closing is a fundamental part of 3D simultaneous localization and mapping (SLAM) that can greatly enhance the quality of long-term mapping. It is essential for the creation of globally consistent maps. Conceptually, loop closing is divided into detection and optimization. Recent approaches depend on a single sensor to recognize previously visited places in the loop detection stage. In this study, we combine data of multiple sensors such as GPS, vision, and laser range data to enhance detection results in repetitively changing environments that are not sufficiently explained by a single sensor. We present a fast and robust hierarchical loop detection algorithm for outdoor robots to achieve a reliable environment representation even if one or more sensors fail.

关键词： ring closing Detection algorithms Loops Robot Sensors Outdoors simultaneous localization and mapping Hierarchical Range of a function

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

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

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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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Optimizing a Mobile Robot Control System using GPU Acceleration

Optimizing a Mobile Robot Control System using GPU Accelerat...

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Conference on intelligent robots and computer vision XXIX - algorithms and techniques

作者： Tuck, Nat McGuinness, Michael Martin, Fred Univ Massachusetts Lowell Lowell MA 01854 USA

ISBN: (纸本)9780819489487

This paper describes our attempt to optimize a robot control program for the intelligent Ground Vehicle Competition (IGVC) by running computationally intensive portions of the system on a commodity graphics processing unit (GPU). The IGVC Autonomous Challenge requires a control program that performs a number of different computationally intensive tasks ranging from computer vision to path planning. For the 2011 competition our Robot Operating System (ROS) based control system would not run comfortably on the multicore CPU on our custom robot platform. The process of profiling the ROS control program and selecting appropriate modules for porting to run on a GPU is described. A GPU-targeting compiler, Bacon, is used to speed up development and help optimize the ported modules. The impact of the ported modules on overall performance is discussed. We conclude that GPU optimization can free a significant amount of CPU resources with minimal effort for expensive user-written code, but that replacing heavily-optimized library functions is more difficult, and a much less efficient use of time.

关键词： robotics stereo vision GPU acceleration

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

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

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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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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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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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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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