Day 016.2 - controlled linear and angular velocities then...

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Velocity Motion Model 2/10/2012 6 recall that we want the posterior conditional density of the control action u t carrying the robot from pose x t -1 to x t in time Δ t so far the algorithm has computed the required control action needed to carry the robot from position (x y) to position (x’ y’) the control action has been computed assuming the robot moves on a circular arc ) , | ( 1 t t t x u x p t u ˆ
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Velocity Motion Model 2/10/2012 7 the computed heading of the robot is the heading should be the difference is or expressed as an angular velocity θ + = ˆ = = ˆ err ω γ ˆ err err = = t t Line 9, Eq 5.25, 5.28
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Velocity Motion Model 2/10/2012 8 similarly, we can compute the errors of the computed linear and rotational velocities t v v v = = dist ˆ err t = = θ ω ˆ err
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Velocity Motion Model 2/10/2012 9 if we assume that the robot has independent control over its
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Unformatted text preview: controlled linear and angular velocities then the joint density of the errors is what do the individual densities look like? ) ( ) ( ) ( ) , , ( err err err err err err p p v p v p = Velocity Motion Model 2/10/2012 10 the most common noise model is additive zero-mean noise, i.e. we need to decide on other characteristics of the noises spread variance skew skew peakedness kurtosis typically, only the variance is specified the true variance is typically unknown + = noise noise v v v actual velocity commanded velocity noise...
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This note was uploaded on 02/13/2012 for the course CSE 4421 taught by Professor Burton during the Winter '11 term at York University.

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Day 016.2 - controlled linear and angular velocities then...

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