Title

Bio-Inspired Varying Subspace Based Computational Framework For A Class Of Nonlinear Constrained Optimal Trajectory Planning Problems

Keywords

bio-inspired method; constrained trajectory planning; optimal trajectory planning

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. © 2014 IOP Publishing Ltd.

Publication Date

1-1-2014

Publication Title

Bioinspiration and Biomimetics

Volume

9

Issue

3

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1088/1748-3182/9/3/036010

Socpus ID

84899496934 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84899496934

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