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A multisine approach for trajectory optimization based on information gain.

Mihaylova, L and De Schutter, J and Bruyninckx, H (2003) A multisine approach for trajectory optimization based on information gain. Robotics and Autonomous Systems, 43 (4). pp. 231-243. ISSN 0921-8890

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    Abstract

    This paper presents amultisine approach for trajectory optimization based on information gain, with distance and orientation sensing to knownbeacons. It addresses the problem of active sensing, i.e. the selection of a robot motion or sequence of motions, which make the robot arrive in its desired goal configuration (position and orientation) with maximum accuracy, given the available sensor information. The optimal trajectory is parameterized as a linear combination of sinusoidal functions. Anappropriate optimality criterion is selected which takes into account various requirements (such as maximum accuracy and minimum time). Several constraints can be formulated, e.g. with respect to collision avoidance. The optimal trajectory is then determined by numerical optimization techniques. The approach is applicable to both nonholonomic and holonomic robots. Its effectiveness is illustrated here for a nonholonomic wheeled mobile robot (WMR) in an environment with and without obstacles.

    Item Type: Article
    Journal or Publication Title: Robotics and Autonomous Systems
    Additional Information: The final, definitive version of this article has been published in the Journal, Robotics and Autonomous Systems, 43 (4), 2003, © ELSEVIER.
    Uncontrolled Keywords: Active sensing ; Mobile robots ; Uncertainty ; Trajectory generation ; Information gain ; DCS-publications-id ; art-754 ; DCS-publications-personnel-id ; 121
    Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
    Departments: Faculty of Science and Technology > School of Computing & Communications
    ID Code: 824
    Deposited By: Dr L Mihaylov
    Deposited On: 21 Jan 2008 14:16
    Refereed?: Yes
    Published?: Published
    Last Modified: 18 Dec 2017 04:19
    Identification Number:
    URI: http://eprints.lancs.ac.uk/id/eprint/824

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