ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

X
feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Electronic Resource
    Electronic Resource
    Entropy-Based Markov Chains for Multisensor Fusion (2000)
    Springer
    Journal of intelligent and robotic systems 29 (2000), S. 161-189 
    Details
    ISSN: 1573-0409
    Keywords: decision making ; entropy ; Markov chains ; multisensor fusion ; uncertainty
    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 This paper proposes an entropy based Markov chain (EMC) fusion technique and demonstrates its applications in multisensor fusion. Self-entropy and conditional entropy, which measure how uncertain a sensor is about its own observation and joint observations respectively, are adopted. We use Markov chain as an observation combination process because of two major reasons: (a) the consensus output is a linear combination of the weighted local observations; and (b) the weight is the transition probability assigned by one sensor to another sensor. Experimental results show that the proposed approach can reduce the measurement uncertainty by aggregating multiple observations. The major benefits of this approach are: (a) single observation distributions and joint observation distributions between any two sensors are represented in polynomial form; (b) the consensus output is the linear combination of the weighted observations; and (c) the approach suppresses noisy and unreliable observations in the combination process.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008138126506
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
  • 2
    Electronic Resource
    Electronic Resource
    Complexity versus Uncertainty: The Question of Staying Alive (2000)
    Springer
    Biology and philosophy 15 (2000), S. 493-508 
    Details
    ISSN: 1572-8404
    Keywords: complexity ; entropy balance ; environment independence ; evolution ; information fundamental identity ; uncertainty
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Philosophy
    Notes: Abstract Some real objects show a very particular tendency: that of becomingindependent with regard to the uncertainty of their surroundings. This isachieved by the exchange of three quantities: matter, energy andinformation. A conceptual framework, based on both Non-equilibriumThermodynamic and the Mathematical Theory of Communication is proposedin order to review the concept of change in living individuals. Three mainsituations are discussed in this context: passive independence inconnection with resistant living forms (such as seeds, spores, hibernation,...), active independence in connection with the life span of aliving individual (whether an ant or an ant farm), and the newindependence in connection with the general debate of biological evolution.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1006611022472
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
  • 3
    Electronic Resource
    Electronic Resource
    a qualitative-connectionist approach to Robotic Spatial Planning: the Peg-in-Hole case study (2000)
    Springer
    Spatial cognition and computation 2 (2000), S. 51-76 
    Details
    ISSN: 1542-7633
    Keywords: connectionist learning ; fine motion ; qualitative spatial reasoning ; robotics ; uncertainty
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Psychology
    Notes: Abstract Qualitative spatial reasoning foractual robots in real-world environments mustnecessarily involve perceptive knowledge, sincecomplete a-priori information of the outerworld can never be assumed, not even at aqualitative level. In this paper a contributionis made towards the integration of quantitativedata – namely, sensor signals – into a higherlevel qualitative plan. This integrationincludes the use of neural networks to learnhow to map complex perceptual signals into aqualitative description. Sensors are used toacquire actual knowledge of the environment andproperly identify, with the help of aconnectionist system, the real state of thesystem. The approach is presented in theframework of robotic tasks involving contactfor which the most informative perception comesfrom force/torque sensors. Empirical simulationresults are provided for the chamferlesstwo-dimensional peg-in-hole insertion modelwith friction. The advantages of learningapproaches over geometric model-basedtechniques are discussed: our approach issimple but robust against unpredictable changesof task parameters, and it exhibits agracefully degrading behavior and on-lineadaptation to new task conditions. Anenhancement to incorporate a measure ofconfidence of the network is also presented.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1011453027703
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
  • 4
    Electronic Resource
    Electronic Resource
    Another Look at the Logical Uncertainty Principle (2000)
    Springer
    Information retrieval 2 (2000), S. 17-26 
    Details
    ISSN: 1573-7659
    Keywords: uncertainty ; information theory ; Bayesian inference ; Ramsey test ; information retrieval model
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract The Logical Uncertainty Principle is re-examined from the point of classical logic. Two interpretations are given, an objective one in terms of an axiomatic theory of information, and a subjective one based on Ramsey's theory of probability.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1009969229281
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
  • 5
    Electronic Resource
    Electronic Resource
    A Probabilistic Approach to Collaborative Multi-Robot Localization (2000)
    Springer
    Autonomous robots 8 (2000), S. 325-344 
    Details
    ISSN: 1573-7527
    Keywords: mobile robots ; localization ; multi-robot systems ; uncertainty
    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 This paper presents a statistical algorithm for collaborative mobile robot localization. Our approach uses a sample-based version of Markov localization, capable of localizing mobile robots in an any-time fashion. When teams of robots localize themselves in the same environment, probabilistic methods are employed to synchronize each robot's belief whenever one robot detects another. As a result, the robots localize themselves faster, maintain higher accuracy, and high-cost sensors are amortized across multiple robot platforms. The technique has been implemented and tested using two mobile robots equipped with cameras and laser range-finders for detecting other robots. The results, obtained with the real robots and in series of simulation runs, illustrate drastic improvements in localization speed and accuracy when compared to conventional single-robot localization. A further experiment demonstrates that under certain conditions, successful localization is only possible if teams of heterogeneous robots collaborate during localization.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008937911390
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
  • 6
    Electronic Resource
    Electronic Resource
    Autonomous Pool Cleaning: Self Localization and Autonomous Navigation for Cleaning (2000)
    Springer
    Autonomous robots 9 (2000), S. 261-270 
    Details
    ISSN: 1573-7527
    Keywords: mobile robot ; underwater environment ; sonar system ; state estimation ; uncertainty
    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 Cleaning is a major problem associated with pools. Since the manual cleaning is tedious and boring there is an interest in automating the task. This paper presents methods for autonomous localization and navigation for a pool cleaner to enable full coverage of pools. Path following cannot be ensured through use of internal position estimation methods alone; therefore sensing is needed. Sensor based estimation enable automatic correction of slippage. For this application we use ultrasonic sonars. Based on an analysis of the overall task and performance of the system a strategy for cleaning/navigation is developed. For the automatic localization a Kalman filtering technique is proposed: the Kalman filter uses sonar measurements and a dynamic model of the robot to provide estimates of the pose of the pool cleaner. Using this localization method we derive an optimal control strategy for traversal of a pool. The system has been implemented and successfully tested on the “WEDAB400” pool cleaner.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008962901812
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...