Trabajo presentado al IROS celebrado en Tokyo del 3 al 7 de noviembre de 2013. ; We propose HRA*, a new randomized path planner for complex 3D environments. The method is a modified A* algorithm that uses a hybrid node expansion technique that combines a random exploration of the action space meeting vehicle kinematic constraints with a cost to goal metric that considers only kinematically feasible paths to the goal. The method includes also a series of heuristics to accelerate the search time. These include a cost penalty near obstacles, and a filter to prevent revisiting configurations. The performance of the method is compared against A*, RRT and RRT* in a series of challenging 3D outdoor datasets. HRA* is shown to outperform all of them in computation time, and delivering shorter paths than A* and RRT. ; This work has been partially supported by the Mexican Council of Science and Technology with a PhD Scholarship to Ernesto Teniente, by the Spanish Ministry of Science and Innovation under project DPI-2011-27510 and by the EU project ARCAS FP7-287617. ; Peer Reviewed


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    Title :

    HRA*: Hybrid randomized path planning for complex 3D environments


    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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