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    Sensor-based Whole-Body Planning/Replanning for Humanoid Robots

    Ferrari, Paolo and Cognetti, Marco and Oriolo, Giuseppe (2019) Sensor-based Whole-Body Planning/Replanning for Humanoid Robots. 2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids). pp. 511-517. ISSN 2164-0580

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    We propose a sensor-based motion planning/replanning method for a humanoid that must execute a task implicitly requiring locomotion. It is assumed that the environment is unknown and the robot is equipped with a depth sensor. The proposed approach hinges upon three modules that run concurrently: mapping, planning and execution. The mapping module is in charge of incrementally building a 3D environment map during the robot motion, based on the information provided by the depth sensor. The planning module computes future motions of the humanoid, taking into account the geometry of both the environment and the robot. To this end, it uses a 2-stages local motion planner consisting in a randomized CoM movement primitives-based algorithm that allows on-line replanning. Previously planned motions are performed through the execution module. The proposed approach is validated through simulations in V-REP for the humanoid robot NAO.

    Item Type: Article
    Keywords: Planning; Robot sensing systems; Humanoid robots; Task analysis; Collision avoidance; Three-dimensional displays;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 15328
    Identification Number:
    Depositing User: Marco Cognetti
    Date Deposited: 24 Jan 2022 16:12
    Journal or Publication Title: 2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids)
    Publisher: IEEE
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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