kor01

rosed [package_name] [filename]
rosed roscpp Logger.msg


# list all editable files
rosed [package_name] <tab><tab>

# set editor
export EDITOR='emacs -nw'

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# record a replay
mkdir relay
cd relay
rosbag record -a

# play back
rosbag play my_bag_files

# twice as fast

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tune alpha value to show axis

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%% get size

d = size(a, 2)
e = size(a, 1)

%% drop singleton dimension
a = squeeze(b)

%% construct

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import matplotlib.image as mpimg
import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline

# Read in and plot the image
image = mpimg.imread('Udacican.jpeg')
plt.imshow(image)

# Take histograms in R, G, and B

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# number of inner corners in x and y direction
nx = 8
ny = 6

#find chessboard corners
img = mpimg.imread(images[idx])

# Convert to grayscale
gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)

kor01

import matplotlib.image as mpimg
import matplotlib.pyplot as plt
import numpy as np
import cv2
import glob
import time
from sklearn.svm import SVC
from sklearn.preprocessing import StandardScaler
# NOTE: the next import is only valid 
# for scikit-learn version <= 0.17

kor01

nosetests --logging-level=WARN -vs

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from the rotor center:

	the pitch surface in phase II and IV: up rotation produce up thrust on the body
    
    the pitch surface in phase I and III: up rotation produce down thrust on the body
    
	up rotation always produce down torque
    
    down rotation produce up torque

kor01

human v.s. robots:

human 3D vision: stereo vision, prior geometry, motion filtering

robot 3D vision: (actively) measure the distance

sensor types:

active sensors: use an enery source to probe the environment