Presentado al 6th ECMR celebrado en Barcelona del 25 al 27 de septiembre de 2013. ; We present a mobile robot exploration strategy that computes trajectories that minimize both path and map entropies. The method evaluates joint entropy reduction and computes a potential field in robot configuration space using these joint entropy reduction estimates. The exploration trajectory is computed descending on the gradient of these field. The technique uses Pose SLAM as its estimation backbone. Very efficient kernel convolution mechanisms are used to evaluate entropy reduction for each sensor ray, and for each possible robot orientation, taking frontiers and obstacles into account. In the end, the computation of this field on the entire C-space is shown to be very efficient computationally. The approach is tested in simulations in a common publicly available dataset comparing favorably both in quality of estimates and execution time against another entropy reduction strategy that uses occupancy maps. ; This work has been supported by the Spanish Ministry of Economy and Competitiveness under Project DPI-2011-27510 and by the EU Project ARCAS FP7-287617. ; Peer Reviewed


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    Title :

    Mobile robot exploration with potential information fields


    Contributors:

    Publication date :

    2013-01-01



    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    DDC:    629



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