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

共 723 条记录，以下是71-80 订阅

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SimTrack: A simulation-based framework for scalable real-time object pose detection and tracking

SimTrack: A simulation-based framework for scalable real-tim...

引用

IEEE/RSJ International Conference on intelligent robots and Systems

作者： K. Pauwels D. Kragic Computer Vision and Active Perception Lab KTH Royal Institute of Technology Stockholm Sweden

We propose a novel approach for real-time object pose detection and tracking that is highly scalable in terms of the number of objects tracked and the number of cameras observing the scene. Key to this scalability is a high degree of parallelism in the algorithms employed. The method maintains a single 3D simulated model of the scene consisting of multiple objects together with a robot operating on them. This allows for rapid synthesis of appearance, depth, and occlusion information from each camera viewpoint. This information is used both for updating the pose estimates and for extracting the low-level visual cues. The visual cues obtained from each camera are efficiently fused back into the single consistent scene representation using a constrained optimization method. The centralized scene representation, together with the reliability measures it enables, simplify the interaction between pose tracking and pose detection across multiple cameras. We demonstrate the robustness of our approach in a realistic manipulation scenario. We publicly release this work as a part of a general ROS software framework for real-time pose estimation, SimTrack, that can be integrated easily for different robotic applications.

关键词： Cameras Robot vision systems Visualization Robot kinematics Real-time systems

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Multi-scale conditional transition map: Modeling spatial-temporal dynamics of human movements with local and long-term correlations

Multi-scale conditional transition map: Modeling spatial-tem...

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IEEE/RSJ International Conference on intelligent robots and Systems

作者： Zhan Wang P. Jensfelt J. Folkesson Computer Vision and Active Perception Lab The Royal Institute of Technology KTH Stockholm Sweden

This paper presents a novel approach to modeling the dynamics of human movements with a grid-based representation. The model we propose, termed as Multi-scale Conditional Transition Map (MCTMap), is an inhomogeneous HMM process that describes transitions of human location state in spatial and temporal space. Unlike existing work, our method is able to capture both local correlations and long-term dependencies on faraway initiating events. This enables the learned model to incorporate more information and to generate an informative representation of human existence probabilities across the grid map and along the temporal axis for intelligent interaction of the robot, such as avoiding or meeting the human. Our model consists of two levels. For each grid cell, we formulate the local dynamics using a variant of the left-to-right HMM, and thus explicitly model the exiting direction from the current cell. The dependency of this process on the entry direction is captured by employing the Input-Output HMM (IOHMM). On the higher level, we introduce the place where the whole trajectory originated into the IOHMM framework forming a hierarchical input structure to capture long-term dependencies. The capabilities of our method are verified by experimental results from 10 hours of data collected in an office corridor environment.

关键词： Hidden Markov models Correlation Trajectory Adaptation models Nonhomogeneous media robots Heuristic algorithms

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New vision System and Navigation Algorithm for an Autonomous Ground Vehicle

New Vision System and Navigation Algorithm for an Autonomous...

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

作者： Tann, Hokchhay Shakya, Bicky Merchen, Alex C. Williams, Benjamin C. Khanal, Abhishek Zhao, Jiajia Ahlgren, David J. Trinity Coll Hartford CT 06106 USA

ISBN: (纸本)9780819499424

Improvements were made to the intelligence algorithms of an autonomously operating ground vehicle, Q, which competed in the 2013 intelligent Ground Vehicle Competition (IGVC). The IGVC required the vehicle to first navigate between two white lines on a grassy obstacle course, then pass through eight GPS waypoints, and pass through a final obstacle field. Modifications to Q included a new vision system with a more effective image processing algorithm for white line extraction. The path-planning algorithm adopted the vision system, creating smoother, more reliable navigation. With these improvements, Q successfully completed the basic autonomous navigation challenge, finishing tenth out of over 50 teams.

关键词： Image Processing Robotics National Instruments LabVIEW Compact RIO Distributed Systems

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Research and Development of Ro-Boat - An Autonomous River Cleaning Robot

Research and Development of Ro-Boat - An Autonomous River Cl...

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

作者： Sinha, Aakash Bhardwaj, Prashant Vaibhav, Bipul Mohammad, Noor Omnipresent Robot Technologies Pvt. Ltd. (India) Manav Rachna College Of Engineering (India) Indian Institute Of Technology Guwahati (India) National Institute Of Technology Warangal (India)

ISBN: (纸本)9780819499424

Ro-Boat is an autonomous river cleaning intelligent robot incorporating mechanical design and computer vision algorithm to achieve autonomous river cleaning and provide a sustainable environment. Ro-boat is designed in a modular fashion with design details such as mechanical structural design, hydrodynamic design and vibrational analysis. It is incorporated with a stable mechanical system with air and water propulsion, robotic arms and solar energy source and it is proceed to become autonomous by using computer vision. Both "HSV Color Space" and "SURF" are proposed to use for measurements in Kalman Filter resulting in extremely robust pollutant tracking. The system has been tested with successful results in the Yamuna River in New Delhi. We foresee that a system of Ro-boats working autonomously 24x7 can clean a major river in a city on about six months time, which is unmatched by alternative methods of river cleaning.

关键词： Autonomous robot River cleaning computer vision Multiple object tracking HSV color space SURF Kalman filter

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3D vision system for intelligent milking robot automation

3D vision system for intelligent milking robot automation

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

作者： Akhloufi, M. A. Ctr Robot & Vis Ind Levis PQ G6V 6Z9 Canada

ISBN: (纸本)9780819499424

In a milking robot, the correct localization and positioning of milking teat cups is of very high importance. The milking robots technology has not changed since a decade and is based primarily on laser profiles for teats approximate positions estimation. This technology has reached its limit and does not allow optimal positioning of the milking cups. Also, in the presence of occlusions, the milking robot fails to milk the cow. These problems, have economic consequences for producers and animal health (e.g. development of mastitis). To overcome the limitations of current robots, we have developed a new system based on 3D vision, capable of efficiently positioning the milking cups. A prototype of an intelligent robot system based on 3D vision for real- time positioning of a milking robot has been built and tested under various conditions on a synthetic udder model (in static and moving scenarios). Experimental tests, were performed using 3D Time-Of-Flight (TOF) and RGBD cameras. The proposed algorithms permit the online segmentation of teats by combing 2D and 3D visual information. The obtained results permit the teat 3D position computation. This information is then sent to the milking robot for teat cups positioning. The vision system has a real-time performance and monitors the optimal positioning of the cups even in the presence of motion. The obtained results, with both TOF and RGBD cameras, show the good performance of the proposed system. The best performance was obtained with RGBD cameras. This latter technology will be used in future real life experimental tests.

关键词： 3D vision multimodal fusion intelligent systems RGBD TOF real-time robotics milking robot.

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The 21TH Annual intelligent Ground Vehicle Competition: Robotists for the Future

The 21TH Annual Intelligent Ground Vehicle Competition: Robo...

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

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

ISBN: (纸本)9780819499424

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 21 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 over 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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Adaptation of human routines to support a robot's tasks planning and scheduling

Adaptation of human routines to support a robot's tasks plan...

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

作者： Tikanmaki, A. Feliu, Troyano S. Roning, J. Univ Oulu CSE Dept Oulu Finland

ISBN: (纸本)9780819499424

Service robots usually share their workspace with people. Typically, a robot's tasks require knowing when and where people are, to be able to schedule requested tasks. Therefore, there exists the need to take into account the presence of humans when planning their actions and it is indispensable to have knowledge of robots' environments. It means in practice knowing when (time and events duration) and where (in workspace) a robot's tasks can be performed. This research paper takes steps towards obtaining of the spatial information required to execute software to plan tasks to be performed by a robot. With this aim, a program capable to define meaningful areas or zones in the robot workspace by the use of a clustering is created tied with statistically reasoned time slots when to perform each task. The software is tested using real data obtained from different cameras located along the corridors of CSE Department of University of Oulu.

关键词： service robots learning clustering

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Self-localization for an Autonomous Mobile Robot Based on an Omni-directional vision System

Self-localization for an Autonomous Mobile Robot Based on an...

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

作者： Chiang, Shu-Yin Lin, Kuang-Yu Chia, Tsorng-Lin Ming Chuan Univ Dept Informat & Telecommun Engn Taoyuan 333 Taiwan Ming Chuan Univ Dept Comp & Commun Engn Taoyuan 333 Taiwan

ISBN: (纸本)9780819499424

In this study, we designed an autonomous mobile robot based on the rules of the Federation of International Robot-soccer Association (FIRA) RoboSot category, integrating the techniques of computer vision, real-time image processing, dynamic target tracking, wireless communication, self-localization, motion control, path planning, and control strategy to achieve the contest goal. The self-localization scheme of the mobile robot is based on the algorithms featured in the images from its omni-directional vision system. In previous works, we used the image colors of the field goals as reference points, combining either dual-circle or trilateration positioning of the reference points to achieve self-localization of the autonomous mobile robot. However, because the image of the game field is easily affected by ambient light, positioning systems exclusively based on color model algorithms cause errors. To reduce environmental effects and achieve the self-localization of the robot, the proposed algorithm is applied in assessing the corners of field lines by using an omni-directional vision system. Particularly in the mid-size league of the RobotCup soccer competition, self-localization algorithms based on extracting white lines from the soccer field have become increasingly popular. Moreover, white lines are less influenced by light than are the color model of the goals. Therefore, we propose an algorithm that transforms the omni-directional image into an unwrapped transformed image, enhancing the extraction features. The process is described as follows: First, radical scan-lines were used to process omni-directional images, reducing the computational load and improving system efficiency. The lines were radically arranged around the center of the omni-directional camera image, resulting in a shorter computational time compared with the traditional Cartesian coordinate system. However, the omni-directional image is a distorted image, which makes it difficult to recognize the

关键词： mobile robot self-localization omni-directional vision dual circle trilateration cross ratio.

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An intelligent Hybrid Behavior Coordination System for an Autonomous Mobile Robot

An Intelligent Hybrid Behavior Coordination System for an Au...

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

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

ISBN: (纸本)9780819499424

In this paper, development of a low-cost PID controller with an intelligent behavior coordination system for an autonomous mobile robot is described that is equipped with IR sensors, ultrasonic sensors, regulator, and RC filters on the robot platform based on HCS12 microcontroller and embedded systems. A novel hybrid PID controller and behavior coordination system is developed for wall-following navigation and obstacle avoidance of an autonomous mobile robot. Adaptive control used in this robot is a hybrid PID algorithm associated with template and behavior coordination models. Software development contains motor control, behavior coordination intelligent system and sensor fusion. In addition, the module-based programming technique is adopted to improve the efficiency of integrating the hybrid PID and template as well as behavior coordination model algorithms. The hybrid model is developed to synthesize PID control algorithms, template and behavior coordination technique for wall-following navigation with obstacle avoidance systems. The motor control, obstacle avoidance, and wall-following navigation algorithms are developed to propel and steer the autonomous mobile robot. Experiments validate how this PID controller and behavior coordination system directs an autonomous mobile robot to perform wall-following navigation with obstacle avoidance. Hardware configuration and module-based technique are described in this paper. Experimental results demonstrate that the robot is successfully capable of being guided by the hybrid PID controller and behavior coordination system for wall-following navigation with obstacle avoidance.

关键词： Behavior coordination system PID controller wall-following navigation obstacle avoidance template-based navigation autonomous mobile robot module-based programming technique

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High-speed object matching and localization using gradient orientation features

High-speed object matching and localization using gradient o...

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

作者： Xu, Xinyu van Beek, Peter Feng, Xiaofan Sharp Labs Amer Camas WA 98607 USA

ISBN: (纸本)9780819499424

In many robotics and automation applications, it is often required to detect a given object and determine its pose (position and orientation) from input images with high speed, high robustness to photometric changes, and high pose accuracy. We propose a new object matching method that improves efficiency over existing approaches by decomposing orientation and position estimation into two cascade steps. In the first step, an initial position and orientation is found by matching with Histogram of Oriented Gradients (HOG), reducing orientation search from 2D template matching to 1D correlation matching. In the second step, a more precise orientation and position is computed by matching based on Dominant Orientation Template (DOT), using robust edge orientation features. The cascade combination of the HOG and DOT feature for high-speed and robust object matching is the key novelty of the proposed method. Experimental evaluation was performed with real-world single-object and multi-object inspection datasets, using software implementations on an Atom CPU platform. Our results show that the proposed method achieves significant speed improvement compared to an already accelerated template matching method at comparable accuracy performance.

关键词： Object matching fast object search fast template matching histogram of oriented gradients dominant orientation template coarse to fine search factory inspection machine vision robotics

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