Target detection in multimodal (multisensor) images is a difficult problem especially with the impact of different views and the complex backgrounds. In this paper, we propose a target detection method based on ground...
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The proceedings contain 29 papers. The topics discussed include: exploiting automatic validation in human mission planning;real-time path planning using a simulation-based Markov decision process;using a plan graph wi...
ISBN:
(纸本)9781447123170
The proceedings contain 29 papers. The topics discussed include: exploiting automatic validation in human mission planning;real-time path planning using a simulation-based Markov decision process;using a plan graph with interaction estimates for probabilistic planning;a hybrid parallel genetic algorithm for the winner determination problem in combinatorial auctions;validation sets, genetic programming and generalisation;a hyper-heuristic approach to evolving algorithms for bandwidth reduction based on genetic programming;two stage speaker verification using self organising map and multilayer perceptron neural network;investigation into computervision methods to extract information for context based image retrieval methods;a multimodal biometric fusion approach based on binary particle optimization;choosing a case base maintenance algorithm using a meta-case base;and 2D mass-spring-like model for prediction of a sponge's behaviour upon robotic interaction.
An intelligent agent operating in the real world needs to be fully aware of the surrounding environment to make the best decision possible at any given point of time. There are many forms of input devices for a robot ...
An intelligent agent operating in the real world needs to be fully aware of the surrounding environment to make the best decision possible at any given point of time. There are many forms of input devices for a robot that gather real-time information of the surroundings, such as video cameras, laser/sonar range finders, and GPS to name a few. In this thesis, a vision system for a mo- bile robot navigating through different illumination conditions is investigated. Many state-of-the-art object recognition algorithms employ methods running on grayscale images, because using color is difficult for several reasons: (a) The object-of-interest's true colors may not be recorded by the camera hardware due to illumination artifacts, and (b) colors are often too ambiguous to be a robust visual descriptor of an object. In this dissertation, we address these two challenges and present new color-based visionalgorithms for mobile robots that are robust and efficient. The first part of this dissertation focuses on the problem of color con- stancy for mobile robots under different lighting conditions. Specifically, We use a generate-and-test methodology to evaluate which simulated global illu- mination condition leads to the generated view that most closely matches what the robot actually sees. We assume the diagonal color model when generating views of the object of interest under previously unseen conditions. In the second part of the dissertation, we present a vision framework for mobile robots that enables observation of illumination artifacts in a scene and reasoning about the lighting conditions to achieve robust color-based object tracking. Before implementing this framework, we first devise a novel vision- based localization correction algorithm with graphics hardware support, and present how to find possibly shaded regions in the recorded scene by using techniques from 3D computer graphics. We then demonstrate how to integrate a color-based object tracker from the first pa
The proceedings contain 32 papers. The topics discussed include: engineering robust intelligentrobots;different micromanipulation applications based on common modular control architecture;recognizing and tracking hum...
ISBN:
(纸本)9780819479327
The proceedings contain 32 papers. The topics discussed include: engineering robust intelligentrobots;different micromanipulation applications based on common modular control architecture;recognizing and tracking humans and vehicles using radar;object tracking by co-trained classifiers and particle filters;teaching and implementing autonomous robotic lab walkthroughs in a biotech laboratory through model-based visual tracking;LandingNav: a precision autonomous landing sensor for robotic platforms on planetary bodies;real-time 3D environment model for obstacle detection and collision avoidance with a mobile service robot;handling of split-and-merge effects and occlusions using feature-based probabilistic data association;robust obstacles detection and tracking using disparity for car driving assistance;and modeling of radial asymmetry in lens distortion facilitated by modern optimization techniques.
Vast mineral resources of precious metals such as gold remain trapped and unexploited due to the lack of economical and practical means of exploration. This requires the development of alternate exploitation technique...
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Vast mineral resources of precious metals such as gold remain trapped and unexploited due to the lack of economical and practical means of exploration. This requires the development of alternate exploitation techniques. Mining robots form a significant alternative to convention mining techniques. However, there are several practical limitations that make such systems difficult to implement in practice. The primary hurdle in realizing such systems is the difficulty in tele-operating the robot under high latency conditions, which is typical of mining of environments. This is further compounded by poor representation of the environment, resulting in reduced situational awareness. The latency in tele-operation can be caused by numerous factors - system latency, compression scheme, communication protocols, constraints on bandwidth, channel contention, poor line of sight and display overhead. This is typically countered by reduction of frame rate or display resolution or quality. This further affects remote navigation of the robot. Non-holistic scene displays further degrade situational perception. This is intricately tied to the effectiveness of the Operator Control Unit (OCU). Besides, improvements in these capabilities without any vehicle intelligence do little in reducing the operator task-load. In this paper, we present the design of a novel augmented virtuality based visualization and operator interface unit along supported by vehicular intelligence, which are targeted at overcoming the above issues. These design considerations and presented algorithms are expected to form the foundation of next generation mining robots.
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 multidiscip...
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ISBN:
(纸本)9780819479327
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 ground vehicle. Teams from around the world focus on developing a suite of dual-use technologies to equip their system of the future with intelligent driving capabilities. Over the past 17 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 70 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.
Spline representations have been successfully used with a genetic algorithm to determine a disparity map for stereo image pairs. This paper describes work to modify the genetic spline algorithm to use a version of the...
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ISBN:
(纸本)9780819479327
Spline representations have been successfully used with a genetic algorithm to determine a disparity map for stereo image pairs. This paper describes work to modify the genetic spline algorithm to use a version of the genetic algorithm with small populations and few generations, previously referred to as "Tiny GAs", to allow algorithm implementations to achieve real-time performance. The algorithm was also targeted at unrectified stereo image pairs to reduce preprocessing making it more suitable for real-time performance. To ensure disparity map quality is preserved, the two dimensional nature of images is maintained to leverage persistent information instead of representing the images as 1-D signals as suggested in the orignal genetic spline algorithm. Experimental results are given of this modified algorithm using unrectified images.
The purpose of this paper is to discuss the challenge of engineering robust intelligentrobots. Robust intelligentrobots may be considered as ones that not only work in one environment but rather in all types of situ...
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ISBN:
(纸本)9780819479327
The purpose of this paper is to discuss the challenge of engineering robust intelligentrobots. Robust intelligentrobots may be considered as ones that not only work in one environment but rather in all types of situations and conditions. Our past work has described sensors for intelligentrobots that permit adaptation to changes in the environment. We have also described the combination of these sensors with a "creative controller" that permits adaptive critic, neural network learning, and a dynamic database that permits task selection and criteria adjustment. However, the emphasis of this paper is on engineering solutions which are designed for robust operations and worst case situations such as day night cameras or rain and snow solutions. This ideal model may be compared to various approaches that have been implemented on "production vehicles and equipment" using Ethernet, CAN Bus and JAUS architectures and to modern, embedded, mobile computing architectures. Many prototype intelligentrobots have been developed and demonstrated in terms of scientific feasibility but few have reached the stage of a robust engineering solution. Continual innovation and improvement are still required. The significance of this comparison is that it provides some insights that may be useful in designing future robots for various manufacturing, medical, and defense applications where robust and reliable performance is essential.
A predictive object detection algorithm was developed to investigate the practicality of using advanced filtering on stereo vision object detection algorithms such as the X-H Map. Obstacle detection with stereo vision...
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ISBN:
(纸本)9780819479327
A predictive object detection algorithm was developed to investigate the practicality of using advanced filtering on stereo vision object detection algorithms such as the X-H Map. Obstacle detection with stereo vision is inherently noisy and non linear. This paper describes the X-H Map algorithm and details a method of improving the accuracy with the Unscented Kalman Filter (UKF). The significance of this work is that it details a method of stereo vision object detection and concludes that the UKF is a relevant method of filtering that improves the robustness of obstacle detection given noisy inputs. This method of integrating the UKF for use in stereo vision is suitable for any standard stereo vision algorithm that is based on pixel matching (stereo correspondence) from disparity maps.
This paper addresses the design, design method, test platform, and test results of an algorithm used in autonomous navigation for intelligent vehicles. The Bluefield State College (BSC) team created this algorithm for...
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ISBN:
(纸本)9780819479327
This paper addresses the design, design method, test platform, and test results of an algorithm used in autonomous navigation for intelligent vehicles. The Bluefield State College (BSC) team created this algorithm for its 2009 intelligent Ground Vehicle Competition (IGVC) robot called Anassa V. The BSC robotics team is comprised of undergraduate computer science, engineering technology, marketing students, and one robotics faculty advisor. The team has participated in IGVC since the year 2000. A major part of the design process that the BSC team uses each year for IGVC is a fully documented "Post-IGVC Analysis." Over the nine years since 2000, the lessons the students learned from these analyses have resulted in an ever-improving, highly successful autonomous algorithm. The algorithm employed in Anassa V is a culmination of past successes and new ideas, resulting in Anassa V earning several excellent IGVC 2009 performance awards, including third place overall. The paper will discuss all aspects of the design of this autonomous robotic system, beginning with the design process and ending with test results for both simulation and real environments.
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