Stochastic Optimal Motion Planning for the Attitude Kinematics of a Rigid Body With Non-Gaussian Uncertainties-Reference-Cited by-同舟云学术

Stochastic Optimal Motion Planning for the Attitude Kinematics of a Rigid Body With Non-Gaussian Uncertainties

Published:2014-10-21 Issue:3 Volume:137 Page:
ISSN:0022-0434
Container-title:Journal of Dynamic Systems, Measurement, and Control
language:en
Short-container-title:

Author:

Lee Taeyoung¹

Affiliation:

1. Assistant Professor Department of Mechanical and Aerospace Engineering, George Washington University, Washington, DC 20052 e-mail:

Abstract

This paper investigates global uncertainty propagation and stochastic motion planning for the attitude kinematics of a rigid body. The Fokker–Planck equation on the special orthogonal group is numerically solved via noncommutative harmonic analysis to propagate a probability density function along flows of the attitude kinematics. Based on this, a stochastic optimal control problem is formulated to rotate a rigid body while avoiding obstacles within uncertain environments in an optimal fashion. The proposed intrinsic, geometric formulation does not require the common assumption that uncertainties are Gaussian or localized. It can be also applied to complex rotational maneuvers of a rigid body without singularities in a unified way. The desirable properties are illustrated by numerical examples.

Publisher

ASME International

Subject

Computer Science Applications,Mechanical Engineering,Instrumentation,Information Systems,Control and Systems Engineering

Link

http://asmedigitalcollection.asme.org/dynamicsystems/article-pdf/doi/10.1115/1.4027950/6118549/ds_137_03_034502.pdf

Reference27 articles.

1. Neighbor List Collision-Driven Molecular Dynamics Simulation for Nonspherical Hard Particles. I. Algorithmic Details;J. Comput. Phys.,2005

2. LaValle, S., and Sharma, R., 1995, “A Framework for Motion Planning in Stochastic Environments: Modeling and Analysis,” Proceedings of the IEEE Conference on Robotics and Automation, pp. 3057–3062.10.1109/ROBOT.1995.525719

3. LaValle, S., and Sharma, R., 1995, “A Framework for Motion Planning in Stochastic Environments: Applications and Computational Issues,” Proceedings of the IEEE Conference on Robotics and Automation, pp. 3063–3068.10.1109/ROBOT.1995.525720

4. The Stochastic Motion Roadmap: A Sampling Framework for Planning With Markov Motion Uncertainty,2007

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