代码搜索：predict
找到约 2,271 项符合「predict」的源代码
代码结果 2,271
www.eeworm.com/read/475660/6775434
m predict.m
function predict (v,g,Q,WB,dt)
%function predict (v,g,Q,WB,dt)
%
% Inputs:
% v, g - control inputs: velocity and gamma (steer angle)
% Q - covariance matrix for velocity and gamma
% WB - v
www.eeworm.com/read/473622/6847356
m predict.m
%PREDICT Apply odometry model for differential drive robot.
% [R,FXR,PATH] = PREDICT(R,ENC,PARAMS)
% calculates the final pose and final pose covariance matrix given
% a start pose, a start pos
www.eeworm.com/read/473622/6847372
m predict.m
%PREDICT Measurement prediction of point features.
% [PR,HR,HM] = PREDICT(P,XR,CR,CRP) transforms the point feature
% P represented in the world frame into the robot frame given the
% uncertain
www.eeworm.com/read/473622/6847416
m predict.m
%PREDICT Measurement prediction of alpha,r-line features.
% [LR,HR,HM] = PREDICT(L,XR,CR,CRL) transforms the alpha,r-line
% feature L represented in the world frame into the robot frame
% given
www.eeworm.com/read/194440/8193679
m predict.m
function prfilt=predict(trin,nop,nlag,stab)
% prfilt= predict(trin,nop,nlag,stab)
% prfilt= predict(trin,nop,nlag)
% prfilt= predict(trin,nop)
%
% PREDICT returns the nop long Wiener prediction
www.eeworm.com/read/293873/8268055
m predict.m
function yp=predict(tb,yb,n,mass,te);
% The 3-DOF Linear System
% functions of generalized state equations
% excitation force acting on the top floor at time k*dt
fk=zeros(n,1);
% load force.
www.eeworm.com/read/293873/8268062
asv predict.asv
function yp=predict(tb,yb,n,mass);
% The 3-DOF Linear System
% functions of generalized state equations
% excitation force acting on the top floor at time k*dt
load force.mat
fk=zeros(n,1);
www.eeworm.com/read/393504/8281447
m predict.m
function particle= predict(particle, V,G,Q, WB,dt, addrandom)
%
% INPUTS:
% xv - vehicle pose sample
% Pv - vehicle pose predict covariance
%
% Note: Pv must be zeroed after each observation
www.eeworm.com/read/393504/8281471
m predict.m
function particle= predict(particle, V,G,Q, WB,dt, addrandom)
%
% INPUTS:
% xv - vehicle pose sample
% Pv - vehicle pose predict covariance
%
% Note: Pv must be zeroed after each observation
www.eeworm.com/read/393504/8281485
m predict.m
function particle= predict(particle, V,G,Q, WB,dt, addrandom)
%
% add random noise to controls
if addrandom == 1
VG= multivariate_gauss([V;G], Q, 1);
V= VG(1); G= VG(2);
end
% predi