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  • 1
    Electronic Resource
    Electronic Resource
    Bradford : Emerald
    Industrial robot 27 (2000), S. 458-467 
    ISSN: 0143-991X
    Source: Emerald Fulltext Archive Database 1994-2005
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Landmark-based navigation of autonomous mobile robots or vehicles has been widely adopted in industry. Such a navigation strategy relies on identification and subsequent recognition of distinctive environment features or objects that are either known a priori or extracted dynamically. This process has inherent difficulties in practice due to sensor noise and environment uncertainty. This paper is to propose a navigation algorithm that simultaneously locates the robots and updates landmarks in a manufacturing environment. A key issue being addressed is how to improve the localization accuracy for mobile robots in a continuous operation, in which the Kalman filter algorithm is adopted to integrate odometry data with scanner data to achieve the required robustness and accuracy. The Kohonen neural networks have been used to recognize landmarks using scanner data in order to initialize and recalibrate the robot position by means of triangulation when necessary.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Bradford : Emerald
    Industrial robot 32 (2005), S. 259-267 
    ISSN: 0143-991X
    Source: Emerald Fulltext Archive Database 1994-2005
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Purpose - This paper presents an evolutionary algorithm (EA) for Sony legged robots to learn good walking behaviours with little or no interaction with the designers. Once the learning method is put into place, the module can learn through its interaction with the real world. Design/methodology/approach - An EA for developing locomotion gaits of quadruped walking robots is presented in this paper. It is based on a hybrid approach that changes the probability of genetic operators in respect to the performance of the operator's offspring. Findings - The mutating and combination behaviours of the genetic algorithms allow the process to develop a useful behaviour over time. The resulting gait from this training proved to be a better solution than the non-interference training for movements over all types of surfaces, pointing to a local optima being discovered in the non-environmental interference situation. Research limitations/implications - The behaviour of these algorithms is stochastic so that they may potentially present different solutions in different runs of the same algorithm. The mechanism described here has several features that should be noted. It allows rapid parameterisation of operator probabilities across the range of potential genetic algorithms and operator set. It is tailored to a steady state reproduction scheme. It would not be literally applicable to problems with noisy evaluation functions. Originality/value - Provides novel application of genetic algorithms to a potentially practical application area.
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Bradford : Emerald
    Assembly automation 21 (2001), S. 143-152 
    ISSN: 0144-5154
    Source: Emerald Fulltext Archive Database 1994-2005
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Today's Internet technology provides a convenient way for us to develop an integrated network environment for the diversified applications of different robotic systems. To be successful in real-world applications, Internet-based robots require a high degree of autonomy and local intelligence to deal with the restricted bandwidth and arbitrary transmission delay of the Internet. This paper describes the first step toward building such an Internet-based robotic system for teleoperation in the University of Essex. The system has a standard network protocol and an interactive human-machine interface. Using a Web browser, a remote operator can control the mobile robot to navigate in our laboratory with visual feedback and a simulated environment map via the Internet. The employment of an intuitive user interface enables Internet users to control the mobile robot and implement useful tasks remotely. Although at its first stage, the developed system has the potential to be extended to many real-world applications such as tele-manufacturing, tele-training and tele-service.
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    Bradford : Emerald
    Industrial robot 28 (2001), S. 45-54 
    ISSN: 0143-991X
    Source: Emerald Fulltext Archive Database 1994-2005
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: It has been an ultimate long-term dream in robotics and AI fields to build robotic systems with life-like appearance, behaviours and intelligence, reflected by many science fiction books and films. This is also an extremely challenging task. This paper introduces our current research efforts to build a multi-agent system for cooperation and learning of multiple life-like robots in the RoboCup domain. A behaviour-based hierarchy is proposed for the Essex Rovers robot football team to achieve intelligent actions in real time, which includes both a neural network-based color detection algorithm and a fuzzy logic controller. Preliminary results based on legged locomotion experiments of Sony walking robots are presented.
    Type of Medium: Electronic Resource
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  • 5
    Electronic Resource
    Electronic Resource
    Springer
    Autonomous robots 1 (1994), S. 69-92 
    ISSN: 1573-7527
    Keywords: mobile robots ; Bayesian approach ; obstacle avoidance ; sensor model
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract Real-time obstacle avoidance is essential for the safe operation of mobile robots in a dynamically changing environment. This paper investigates how an industrial mobile robot can respond to unexpected static obstacles while following a path planned by a global path planner. The obstacle avoidance problem is formulated using decision theory to determine an optimal response based on inaccurate sensor data. The optimal decision rule minimises the Bayes risk by trading between a sidestep maneuver and backtracking to follow an alternative path. Real-time implementation is emphasised here as part of a framework for real world applications. It has been successfully implemented both in simulation and in reality using a mobile robot.
    Type of Medium: Electronic Resource
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  • 6
    Publication Date: 2020-08-27
    Description: The representation and selection of action features directly affect the recognition effect of human action recognition methods. Single feature is often affected by human appearance, environment, camera settings, and other factors. Aiming at the problem that the existing multimodal feature fusion methods cannot effectively measure the contribution of different features, this paper proposed a human action recognition method based on RGB-D image features, which makes full use of the multimodal information provided by RGB-D sensors to extract effective human action features. In this paper, three kinds of human action features with different modal information are proposed: RGB-HOG feature based on RGB image information, which has good geometric scale invariance; D-STIP feature based on depth image, which maintains the dynamic characteristics of human motion and has local invariance; and S-JRPF feature-based skeleton information, which has good ability to describe motion space structure. At the same time, multiple K-nearest neighbor classifiers with better generalization ability are used to integrate decision-making classification. The experimental results show that the algorithm achieves ideal recognition results on the public G3D and CAD60 datasets.
    Print ISSN: 1024-123X
    Electronic ISSN: 1563-5147
    Topics: Mathematics , Technology
    Published by Hindawi
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  • 7
    Publication Date: 2005-11-05
    Print ISSN: 0268-3768
    Electronic ISSN: 1433-3015
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Published by Springer
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  • 8
    Publication Date: 2013-01-07
    Electronic ISSN: 2218-6581
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 9
    Publication Date: 2017-08-17
    Electronic ISSN: 2218-6581
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 10
    Publication Date: 2018-11-01
    Description: Autonomous/unmanned driving is the major state-of-the-art step that has a potential to fundamentally transform the mobility of individuals and goods. At present, most of the developments target standalone autonomous vehicles, which can sense the surroundings and control the vehicle based on this perception, with limited or no driver intervention. This paper focuses on the next step in autonomous vehicle research, which is the collaboration between autonomous vehicles, mainly vehicle formation control or vehicle platooning. To gain a deeper understanding in this area, a large number of the existing published papers have been reviewed systemically. In other words, many distributed and decentralized approaches of vehicle formation control are studied and their implementations are discussed. Finally, both technical and implementation challenges for formation control are summarized.
    Electronic ISSN: 2218-6581
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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