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Raspberry Pi 的代码
mc_stat_distrib.m
function pi = mc_stat_distrib(P)
% MC_STAT_DISTRIB Compute stationary distribution of a Markov chain
% function pi = mc_stat_distrib(P)
%
% Each row of P should sum to one; pi is a column vector
mc_stat_distrib.m
function pi = mc_stat_distrib(P)
% MC_STAT_DISTRIB Compute stationary distribution of a Markov chain
% function pi = mc_stat_distrib(P)
%
% Each row of P should sum to one; pi is a column vector
% K
predict_true.m
function xv= predict_true(xv, V,G, WB,dt)
%
% INPUTS:
xv= [xv(1) + V*dt*cos(G+xv(3,:));
xv(2) + V*dt*sin(G+xv(3,:));
pi_to_pi(xv(3) + V*dt*sin(G)/WB)];
predict_true.m
function xv= predict_true(xv, V,G, WB,dt)
%
% INPUTS:
xv= [xv(1) + V*dt*cos(G+xv(3,:));
xv(2) + V*dt*sin(G+xv(3,:));
pi_to_pi(xv(3) + V*dt*sin(G)/WB)];
mc_stat_distrib.m
function pi = mc_stat_distrib(P)
% MC_STAT_DISTRIB Compute stationary distribution of a Markov chain
% function pi = mc_stat_distrib(P)
%
% Each row of P should sum to one; pi is a column vector
% K
fuliyebian.m
%ti xing bo fu li ye zhan kai
clear;
clc;
close all;
format long;
AA=42975;
zhuansu=1000;
d=60.0/zhuansu/360*3.0;
w=2*pi*zhuansu/60;
a=63
k=(1:2:91);
n1=length(k);
t=(0:0.001:6.5);
tx1
zonghemoxing.asv
clear all;
clc;
close all;
format long;
a=pi/2;
h=0.001;
t=5;
w=2*pi*100;
bt=rem(t,h);
bbt=t-bt;
n1=bbt/h;
k=0;
for i=1:n1
t(:,i)=(i-1)*h;
oo=w*t(:,i)/60;
if oo
trajactory.asv
L0=0;L(1)=0;L(2)=3.72;L(3)=1.62;L(4)=1.05;x0=6;xf=3.5;z0=-2;zf=-2;%挖掘机参数
af=atan((z0-zf)./(x0-xf));%判断所给直线的角度，或者直接给出直线的角度，则更加的方便！
%while 23*pi/180
mc_stat_distrib.m
function pi = mc_stat_distrib(P)
% MC_STAT_DISTRIB Compute stationary distribution of a Markov chain
% function pi = mc_stat_distrib(P)
%
% Each row of P should sum to one; pi is a column vector