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

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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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Financialized methods for market-based multi-sensor fusion

Financialized methods for market-based multi-sensor fusion

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IEEE/RSJ International Conference on intelligent robots and Systems

作者： J. Abernethy M. Johnson-Roberson Department of Electrical Engineering & Computer Science University of Michigan Ann Arbor MI USA Department of Naval Architecture & Marine Engineering University of Michigan Ann Arbor MI USA

Autonomous systems rely on an increasing number of input sensors of various modalities, and the problem of sensor fusion has received attention for many years. Autonomous system architectures are becoming more complex with time, and the number and placement of sensors will be modified regularly, sensors will fail for many reasons, information will arrive asynchronously, and the system will need to adjust to rapidly changing environments. To address these issues we propose a new paradigm for fusing information from multiple sources that draws from the rich of field pertaining to financial markets, particularly recent research on prediction market design. Among the many benefits of this financialized approach is that, both in theory and in practice, markets are well-equipped to robustly synthesize information from diverse sources in a decentralized fashion. Our framework poses sensor processing algorithms as profit-seeking market participants, data is incorporated via financial transactions, and the joint estimation is represented as a price equilibrium. We use pedestrian detection as a motivating application. Pedestrian detection is a well studied field and essential to autonomous driving. Real world fusion results are presented on RGB and LIDAR data from the KITTI vision Benchmark Suite. We demonstrate we can achieve comparable performance to state-of-the-art hand designed fusion techniques using the proposed approach.

关键词： Sensor fusion Contracts Sensor systems Bayes methods Robot kinematics

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Motion lecture annotation system to learn Naginata performances

Motion lecture annotation system to learn Naginata performan...

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

作者： Kobayashi, Daisuke Sakamoto, Ryota Nomura, Yoshihiko Mie Univ Grad Sch Engn 1577 Kurima Machiya Tsu Mie Japan Mie Univ Hosp Tsu Mie Japan

ISBN: (纸本)9780819499424

This paper describes a learning assistant system using motion capture data and annotation to teach "Naginata-jutsu" (a skill to practice Japanese halberd) performance. There are some video annotation tools such as YouTube. However these video based tools have only single angle of view. Our approach that uses motion-captured data allows us to view any angle. A lecturer can write annotations related to parts of body. We have made a comparison of effectiveness between the annotation tool of YouTube and the proposed system. The experimental result showed that our system triggered more annotations than the annotation tool of YouTube.

关键词： Sports Instruction Motion Capture Virtual Reality e-Learning Annotation Human computer Interaction

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Discrete and Continuous Curvature Computation for Real Data

Discrete and Continuous Curvature Computation for Real Data

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

作者： Colbry, Dirk Shrikhande, Neelima Michigan State Univ E Lansing MI 48824 USA Cent Michigan Univ Mt Pleasant MI 48858 USA

ISBN: (纸本)9780819499424

This paper describes two methods for estimating the minimum and maximum curvatures for a 3D surface and compares the computational efficiency of these approaches on 3D sensor data. The classical method of Least Square Fitting (LSF) finds an approximation of a cubic polynomial fit for the local surface around the point of interest P and uses the coefficients to compute curvatures. The Discrete Differential Geometry (DDG) algorithm approximates a triangulation of the surface around P and calculates the angle deficit at P as an estimate of the curvatures. The accuracy and speed of both algorithms are compared by applying them to synthetic and real data sets with sampling neighborhoods of varying sizes. Our results indicate that the LSF and DDG methods produce comparable results for curvature estimations but the DDG method performs two orders of magnitude faster, on average. However, the DDG algorithm is more susceptible to noise because it does not smooth the data as well as the LSF method. In applications where it is not necessary for the curvatures to be precise (such as estimating anchor point locations for face recognition) the DDG method yields similar results to the LSF method while performing much more efficiently.

关键词： 3D scanning Strontium Optical spheres Statistical analysis Facial recognition systems computer graphics Detection and tracking algorithms Evolutionary algorithms Image processing 3D modeling

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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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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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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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Color Back Projection for Fruit Maturity Evaluation

Color Back Projection for Fruit Maturity Evaluation

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

作者： Zhang, Dong Lee, Dah-Jye Desai, Alok Sun Yat Sen Univ Sch Informat Sci & Technol Guangzhou 510006 Guangdong Peoples R China Brigham Young Univ Dept Elect & Comp Engn Provo UT 84602 USA

ISBN: (纸本)9780819499424

In general, fruits and vegetables such as tomatoes and dates are harvested before they fully ripen. After harvesting, they continue to ripen and their color changes. Color is a good indicator of fruit maturity. For example, tomatoes change color from dark green to light green and then pink, light red, and dark red. Assessing tomato maturity helps maximize its shelf life. Color is used to determine the length of time the tomatoes can be transported. Medjool dates change color from green to yellow, and the orange, light red and dark red. Assessing date maturity helps determine the length of drying process to help ripen the dates. Color evaluation is an important step in the processing and inventory control of fruits and vegetables that directly affects profitability. This paper presents an efficient color back projection and image processing technique that is designed specifically for real-time maturity evaluation of fruits. This color processing method requires very simple training procedure to obtain the frequencies of colors that appear in each maturity stage. This color statistics is used to back project colors to predefined color indexes. Fruit maturity is then evaluated by analyzing the reprojected color indexes. This method has been implemented and used for commercial production.

关键词： Machine vision color back projection color grading tomatoes non-contact visual inspection

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An Effective Trace-Guided Wave-front Navigation and Map Building Approach for Autonomous Mobile robots

An Effective Trace-Guided Wave-front Navigation and Map Buil...

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

作者： Luo, Chaomin Krishnan, Mohan Paulik, Mark Jan, Gene Eu Univ Detroit Mercy Dept Elect & Comp Engn Detroit MI 48221 USA Natl Taipei Univ Inst Elect Engn Taipei Taiwan

ISBN: (纸本)9780819499424

This paper aims to address a trace- guided real-time navigation and map building approach of an autonomous mobile robot. Wave-front based global path planner is developed to generate a global trajectory for an autonomous mobile robot. Modified Vector Field Histogram (M-VFH) is employed based on the LIDAR sensor information to guide the robot locally to be autonomously traversed with obstacle avoidance by following traces provided by the global path planner. A local map composed of square grids is created through the local navigator while the robot traverses with limited LIDAR sensory information. From the measured sensory information, a map of the robot's immediate limited surroundings is dynamically built for the robot navigation. The real-time wave-front based navigation and map building methodology has been successfully demonstrated in a Player/Stage simulation environment. With the wave-front-based global path planner and M-VFH local navigator, a safe, short, and reasonable trajectory is successfully planned in a majority of situations without any templates, without explicitly optimizing any global cost functions, and without any learning procedures. Its effectiveness, feasibility, efficiency and simplicity of the proposed real-time navigation and map building of an autonomous mobile robot have been successfully validated by simulation and comparison studies. Comparison studies of the proposed approach with the other path planning approaches demonstrate that the proposed method is capable of planning more reasonable and shorter collision-free trajectories autonomously.

关键词： Wave-front path planning trace-guided navigation map building global path panning LIDAR-based navigator

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Using Short-wave Infrared Imaging for Fruit Quality Evaluation

Using Short-wave Infrared Imaging for Fruit Quality Evaluati...

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

作者： Zhang, Dong Lee, Dah-Jye Desai, Alok Sun Yat Sen Univ Sch Informat Sci & Technol Guangzhou 510006 Guangdong Peoples R China Brigham Young Univ Dept Elect & Comp Engn Provo UT 84602 USA

ISBN: (纸本)9780819499424

Quality evaluation of agricultural and food products is important for processing, inventory control, and marketing. Fruit size and surface quality are two important quality factors for high-quality fruit such as Medjool dates. Fruit size is usually measured by length that can be done easily by simple image processing techniques. Surface quality evaluation on the other hand requires more complicated design, both in image acquisition and image processing. Skin delamination is considered a major factor that affects fruit quality and its value. This paper presents an efficient histogram analysis and image processing technique that is designed specifically for real-time surface quality evaluation of Medjool dates. This approach, based on short-wave infrared imaging, provides excellent image contrast between the fruit surface and delaminated skin, which allows significant simplification of image processing algorithm and reduction of computational power requirements. The proposed quality grading method requires very simple training procedure to obtain a gray scale image histogram for each quality level. Using histogram comparison, each date is assigned to one of the four quality levels and an optimal threshold is calculated for segmenting skin delamination areas from the fruit surface. The percentage of the fruit surface that has skin delamination can then be calculated for quality evaluation. This method has been implemented and used for commercial production and proven to be efficient and accurate.

关键词： Machine vision histogram analysis fruit grading Medjool date non-contact visual inspection short-wave infrared imaging

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