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Statements

Subject Item
dbr:Linear-quadratic_regulator_rapidly-exploring_random_tree
rdfs:label
Linear-quadratic regulator rapidly-exploring random tree
rdfs:comment
Linear-quadratic regulator rapidly-exploring random tree (LQR-RRT) is a sampling based algorithm for kinodynamic planning. A solver is producing random actions which are forming a funnel in the state space. The generated tree is the action sequence which fulfills the cost function. The restriction is, that a prediction model, based on differential equations, is available to simulate a physical system.
dbp:name
LQR-RRT
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dbc:Optimal_control dbc:Search_algorithms
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64483868
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1090830125
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dbr:Differential_equation dbr:Underactuation dbr:State_space dbc:Search_algorithms dbc:Optimal_control n7:MPC_scheme_basic.svg dbr:Control_theory n7:Cart-pendulum.svg dbr:Time_horizon dbr:Newton's_laws_of_motion dbr:Kinodynamic_planning dbr:Model_predictive_control dbr:PID_controller dbr:Trajectory_(disambiguation) dbr:Linear-quadratic_regulator
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O
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dbp:caption
Finds a trajectory for an underactuated system
dbp:class
Kinodynamic motion planning
dbp:time
O
dbo:abstract
Linear-quadratic regulator rapidly-exploring random tree (LQR-RRT) is a sampling based algorithm for kinodynamic planning. A solver is producing random actions which are forming a funnel in the state space. The generated tree is the action sequence which fulfills the cost function. The restriction is, that a prediction model, based on differential equations, is available to simulate a physical system.
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wikipedia-en:Linear-quadratic_regulator_rapidly-exploring_random_tree
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dbr:Linear-quadratic_regulator_rapidly-exploring_random_tree