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.
In this paper we describe a real-time 3D environment model for obstacle detection and collision avoidance with a mobile service robot. It is fully integrated in the experimental platform DESIRE. Experiments show, that...
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ISBN:
(纸本)9780819479327
In this paper we describe a real-time 3D environment model for obstacle detection and collision avoidance with a mobile service robot. It is fully integrated in the experimental platform DESIRE. Experiments show, that all components perform well and allow for reliable and robust operation of a mobile service robot with actuating capabilities in the presence of obstacles.
A possibility to reduce the investment costs is an improved functionality of the inspection station in order to awaken investors' interest to buy. A new concept for 2-D and 3-D metric and logical quality monitorin...
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ISBN:
(纸本)9780819479327
A possibility to reduce the investment costs is an improved functionality of the inspection station in order to awaken investors' interest to buy. A new concept for 2-D and 3-D metric and logical quality monitoring with a more accurate, flexible, economical and efficient inspection station has been developed and tested at IITB. The inspection station uses short- and wide-range sensors, an intelligent grip system and a so-called "sensor magazine" which make the inspection process more flexible. The sensor magazine consists of various sensor ports with various task-specific, interchangeable sensors. With the sensor magazine and the improved measuring methods, the testing periods and therefore the costs in factory can be substantially decreased.
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.
A single-camera stereo vision system offers a greatly simplified approach to image capture and analysis. In the original study by Lovegrove and Brame, they proposed a novel optical system that uses a single camera to ...
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ISBN:
(纸本)9780819479327
A single-camera stereo vision system offers a greatly simplified approach to image capture and analysis. In the original study by Lovegrove and Brame, they proposed a novel optical system that uses a single camera to capture two short, wide stereo images that can then be analyzed for real-time obstacle detection. In this paper, further analysis and refinement of the optical design results in two virtual cameras with perfectly parallel central axes. A new prototype camera design provides experimental verification of the analysis and also provides insight into practical construction. The experimental device showed that the virtual cameras' axes possessed a deviation from parallel of less than 12 minutes (or 0.2 degrees). The calculation of distances to objects from the two overlapping images all showed errors smaller than the pixel resolution limitation. In addition, a barrel lens correction was used in processing the image to allow parallax distance determination in the whole horizontal view of the images.
A mobile robot moving in an environment in which there are other moving objects and active agents, some of which may represent threats and some of which may represent collaborators, needs to be able to reason about th...
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ISBN:
(纸本)9780819479327
A mobile robot moving in an environment in which there are other moving objects and active agents, some of which may represent threats and some of which may represent collaborators, needs to be able to reason about the potential future behaviors of those objects and agents. In previous work, we presented an approach to tracking targets with complex behavior, leveraging a 3D simulation engine to generate predicted imagery and comparing that against real imagery. We introduced an approach to compare real and simulated imagery using an affine image transformation that maps the real scene to the synthetic scene in a robust fashion. In this paper, we present an approach to continually synchronize the real and synthetic video by mapping the affine transformation yielded by the real/synthetic image comparison to a new pose for the synthetic camera. We show a series of results for pairs of real and synthetic scenes containing objects including similar and different scenes.
Submarine oil and gas pipeline inspection is a highly time and cost consuming task. Using an autonomous underwater vehicle (AUV) for such applications represents a great saving potential. However, the AUV navigation s...
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ISBN:
(纸本)9780819479327
Submarine oil and gas pipeline inspection is a highly time and cost consuming task. Using an autonomous underwater vehicle (AUV) for such applications represents a great saving potential. However, the AUV navigation system requires reliable localization and stable tracking of the pipeline position. We present a method for robust pipeline localization relative to the AUV in 3D based on stereo vision and echo sounder depth data. When the pipe is present in both camera images, a standard stereo vision approach is used for localization. Enhanced localization continuity is ensured using a second approach when the pipe is segmented out in only one of the images. This method is based on a combination of one camera with depth information from the echo sounder mounted on the AUV. In the algorithm, the plane spanned by the pipe in the camera image is intersected with the plane spanned by the sea floor, to give the pipe position in 3D relative to the AUV. Closed water recordings show that the proposed method localizes the pipe with an accuracy comparable to that of the stereo vision method. Furthermore, the introduction of a second pipe localization method increases the true positive pipe localization rate by a factor of four.
Most current lens distortion models use only a few terms of Brown's model, which assumes that the radial distortion is dependant only on the distance from the distortion centre, and an additive tangential distorti...
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ISBN:
(纸本)9780819479327
Most current lens distortion models use only a few terms of Brown's model, which assumes that the radial distortion is dependant only on the distance from the distortion centre, and an additive tangential distortion can be used to correct lens de-centering. This paper shows that the characterization of lens distortion can be improved by over 79% compared to prevailing methods. This is achieved by using modern numerical optimization techniques such as the Leapfrog algorithm, and sensitivity-normalized parameter scaling to reliably and repeatably determine more terms for Brown's model. An additional novel feature introduced in this paper is to allow the distortion to vary not only with polar distance but with the angle too. Two models for radially asymmetrical distortion (i.e. distortion that is dependant on both polar angle and distance) are discussed, implemented and contrasted to results obtained when no asymmetry is modelled. A sample of 32 cameras exhibiting extreme barrel distortion (due to their 6.0mm focal lengths) is used to show that these new techniques can straighten lines to within 7 hundredths of a pixel RMS over the entire image.
In this paper, we present Argos, an autonomous ground robot built for the 2009 intelligent Ground Vehicle Competition (IGVC). Discussed are the significant improvements over its predecessor from the 2008 IGVC, Kratos....
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ISBN:
(纸本)9780819479327
In this paper, we present Argos, an autonomous ground robot built for the 2009 intelligent Ground Vehicle Competition (IGVC). Discussed are the significant improvements over its predecessor from the 2008 IGVC, Kratos. We continue to use stereo visiontechniques to generate a cost map of the environment around the robot. Lane detection is improved through the use of color filters that are robust to changing lighting conditions. The addition of a single-axis gyroscope to the sensor suite allows accurate measurement of the robot's yaw rate and compensates for wheel slip, vastly improving state estimation. The combination of the D* Lite algorithm, which avoids unnecessary re-planning, and the Field D* algorithm, which allows us to plan much smoother paths, results in an algorithm that produces higher quality paths in the same amount of time as methods utilizing A*. The successful implementation of a crosstrack error navigation law allows the robot to follow planned paths without cutting corners, reducing the chance of collision with obstacles. A redesigned chassis with a smaller footprint and a bi-level design, combined with a more powerful drivetrain, makes Argos much more agile and maneuverable compared to its predecessor. At the 2009 IGVC, Argos placed first in the Navigation Challenge.
Increased interest in the exploration of extra terrestrial planetary bodies calls for an increase in the number of spacecraft landing on remote planetary surfaces. Currently, imaging and radar based surveys are used t...
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ISBN:
(纸本)9780819479327
Increased interest in the exploration of extra terrestrial planetary bodies calls for an increase in the number of spacecraft landing on remote planetary surfaces. Currently, imaging and radar based surveys are used to determine regions of interest and a safe landing zone. The purpose of this paper is to introduce LandingNav, a sensor system solution for autonomous landing on planetary bodies that enables landing on unknown terrain. LandingNav is based on a novel multiple field of view imaging system that leverages the integration of different state of the art technologies for feature detection, tracking, and 3D dense stereo map creation. In this paper we present the test flight results of the LandingNav system prototype. Sources of errors due to hardware limitations and processing algorithms were identified and will be discussed. This paper also shows that addressing the issues identified during the post-flight test data analysis will reduce the error down to 1-2%, thus providing for a high precision 3D range map sensor system.
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