Tree Based Trajectory Optimization Based on Local Linearity of Continuous Non-Linear Dynamics

Chyon Hae Kim, Shigeki Sugano

    Research output: Contribution to journalArticle

    8 Citations (Scopus)

    Abstract

    This technical note addresses a tradeoff in the tree based trajectory optimization algorithms for open-loop optimal control problem of rigid body system. In this technical note, linear prediction based uniform state sampling method (LPUSS), which relaxes the tradeoff between solutions' quality and computational efficiency, is proposed on the basis of the local linearity of motion equations. LPUSS has a lower calculation order than randomized kinodynamic planning (RKP) and rapid semi-optimal motion planning (RASMO). In the validation using multi degree-of-freedom (DOF) under actuated manipulator models, the solutions' quality and the computational efficiency of LPUSS were better than those of RKP and RASMO. LPUSS finished the optimization for the 6 DOF model within 40 minutes. This was the world's first success of the optimization of the swing up motion of a 6 DOF under actuated manipulator model.

    Original languageEnglish
    Article number7322197
    Pages (from-to)2610-2617
    Number of pages8
    JournalIEEE Transactions on Automatic Control
    Volume61
    Issue number9
    DOIs
    Publication statusPublished - 2016 Sep 1

    Fingerprint

    Trajectories
    Sampling
    Motion planning
    Computational efficiency
    Manipulators
    Planning
    Trees (mathematics)
    Equations of motion

    Keywords

    • Degree-of-freedom (DOF)
    • linear prediction based uniform state sampling method (LPUSS)
    • randomized kinodynamic planning (RKP)
    • rapid semi-optimal motion planning (RASMO)

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • Computer Science Applications
    • Electrical and Electronic Engineering

    Cite this

    Tree Based Trajectory Optimization Based on Local Linearity of Continuous Non-Linear Dynamics. / Kim, Chyon Hae; Sugano, Shigeki.

    In: IEEE Transactions on Automatic Control, Vol. 61, No. 9, 7322197, 01.09.2016, p. 2610-2617.

    Research output: Contribution to journalArticle

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