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Optimal Sampling-Based Planning for Linear-Quadratic Kinodynamic Systems Gustavo Goretkin1 , Alejandro Perez1 , Robert Platt Jr.2 , and George Konidaris1 Abstract—We propose a new method for applying RRT∗ to kinodyna
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Document Date: 2013-02-27 20:38:43

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File Size: 2,36 MB

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City

Optimal Sampling / Atlanta / Sampling / /

Company

Draper / Cambridge University Press / Artificial Intelligence Laboratory / /

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Facility

Massachusetts Institute of Technology / The State University / Engineering University / /

Holiday

Assumption / /

IndustryTerm

double integrator / kinodynamic systems / affine systems / near-optimal solutions / non-linear systems / lowest cost solution / linear-quadratic systems / arbitrary affine dynamical systems / search tree / candidate solutions / Note solutions / linear systems / affine kinodynamic systems / twodimensional double integrator / kinematic systems / /

Organization

Cambridge University / National Science Foundation / Singapore-MIT International Design Center / Massachusetts Institute of Technology / Computer Science and Engineering University / Singapore Ministry of Education / State University of New York / /

Person

Robert Platt Jr. / /

Position

author / linearized LQR controller / infinite-horizon LQR controller / controller / /

Product

Riccati / /

ProvinceOrState

Georgia / Massachusetts / /

Technology

Sampling-based algorithms / The algorithm / RRT-based algorithms / RRT algorithm / The RRT algorithm / /

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