Bio-inspired varying subspace based computational framework for a class of nonlinear constrained optimal trajectory planning problems

    Authors

    Y. Xu;N. Li

    Comments

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    Abbreviated Journal Title

    Bioinspir. Biomim.

    Keywords

    constrained trajectory planning; bio-inspired method; optimal trajectory; planning; VIRTUAL MOTION CAMOUFLAGE; COSTATE ESTIMATION; OPTIMIZATION; CONVERGENCE; COLLOCATION; STRATEGY; PURSUIT; STATE; PREY; Engineering, Multidisciplinary; Materials Science, Biomaterials; Robotics

    Abstract

    Biological species have produced many simple but efficient rules in their complex and critical survival activities such as hunting and mating. A common feature observed in several biological motion strategies is that the predator only moves along paths in a carefully selected or iteratively refined subspace (or manifold), which might be able to explain why these motion strategies are effective. In this paper, a unified linear algebraic formulation representing such a predator-prey relationship is developed to simplify the construction and refinement process of the subspace (or manifold). Specifically, the following three motion strategies are studied and modified: motion camouflage, constant absolute target direction and local pursuit. The framework constructed based on this varying subspace concept could significantly reduce the computational cost in solving a class of nonlinear constrained optimal trajectory planning problems, particularly for the case with severe constraints. Two non-trivial examples, a ground robot and a hypersonic aircraft trajectory optimization problem, are used to show the capabilities of the algorithms in this new computational framework.

    Journal Title

    Bioinspiration & Biomimetics

    Volume

    9

    Issue/Number

    3

    Publication Date

    1-1-2014

    Document Type

    Article

    Language

    English

    First Page

    13

    WOS Identifier

    WOS:000342116600012

    ISSN

    1748-3182

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