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During last few lessons, we have analyzed both geometrical and analytical Jacobean mattresses.

2
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Both of them enable us to get the end effector velocities, given joint velocities especially less less

3
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than we have seen analytical Jacobean during driving analytical Jacobean formulation.

4
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We have seen this matrix and it called it matrix speed, which was a function of our P y angles.

5
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So pitch your angles, then we have used it during the duration of the Jacobean matrix.

6
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More clearly, we have used its inverse.

7
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But as you know, the inverse of mattresses is such a notion that we have to be careful.

8
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So we have to ask whether it be matrix is always inverted or not.

9
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And if you analyze metrics, speak carefully, you will see that it is not the case because it's obvious

10
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from the definition of Matrix beat that when pitch angle P is equal to plus minus pi over two or plus

11
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minus 90 degrees, then we have cosine p zero, which makes first and third columns of the B matrix

12
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the same.

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So they become linear dependent and the matrix becomes rank deficient so we cannot get its inverse.

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This case is called a representational singularity, while during last lessons we have tried to get

15
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and the factor velocities given joint velocities.

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However, it is much more interesting for us to know what should be the joint velocities in order to

17
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get the desired and the fact that the velocity so we have to use the inverse of Jacobean matrix.

18
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Now we are faced with again the same problem.

19
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Does the Jacobean always in vertical?

20
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And again, the answer is no, as all the Jacobin matrix is configuration dependent.

21
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There will be some cases in which the Jacobean matrix will be singular.

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Other than that, we will assume that we have six degrees of freedom robot manipulator because, as

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you know, in this case, our Jacobean matrix will be square and square mattresses are inevitable.

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I don't consider the case left inverse of mattresses.

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OK?

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Anyway, let's continue.

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The Jacobean will be singular.

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When it's determinant will be zero.

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Finding the case has been Jacobean is singular is important for us because these cases represent robot

30
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manipulators configurations in which motion in certain directions are unachievable.

31
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Other than that, during singularities bounded and the vector velocities make or respond to a mound

32
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the joint velocities.

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We want to avoid this situation because it's damaging for our robot manipulator.

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Also, singularities happened when the robot reaches its maximum of boundaries in work space, which

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can be referred as singularity to.

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Also, singularities happen when one or more axis has become aligned that referred us that causes loss

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of degree of freedom, namely Gimbel look problem that we have seen earlier.

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This can be called singularity.

39
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Now let's jump to the MATLAB and try to investigate that problem more deeply.

40
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OK, now let's try to understand singularities by using MATLAB Pethokoukis Library.

41
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So let's first drug import Puma five 16.

42
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Excuse me, robot manipulator.

43
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OK, its model.

44
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So first, let's calculate its Jacobean saw p five six.

45
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The thought um, jakob's zero.

46
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OK, this is the common for calculating Jacobean of a robot manipulator.

47
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So we calculated the Jacobean of our Puma five six model at when Jones R Q R, so in a ready position.

48
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OK, this is our, as you can see, Jacobean now.

49
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I want you to analyze this Jacobean.

50
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As you can see, this Jacobean consists of six rows and six columns, which is normal because our robot

51
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manipulator is six degrees of freedom.

52
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So it's square.

53
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But is it invert?

54
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Let's investigate.

55
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As you can see, we have the fourth.

56
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Six joints.

57
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OK.

58
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Are joint fourth and so forth, and six columns are linearly dependent.

59
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OK.

60
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As you can see, both of them, we have learned the meaning of Jacobean last time.

61
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So as you know, this means that the fourth and six joints of our robot affects only the orientation

62
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in the z direction of our end manipulator about that direction.

63
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Why?

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Because these are the wrist.

65
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OK.

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These are these constitute our wrists for fifth and sixth

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joints.

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So as fourth and sixth joints are linearly independent, so columns excuse me, columns are linearly

69
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independent.

70
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Our Jacobin is singular.

71
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OK, so rank deficient.

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Let's are our determinant of our Jacobean should be zero.

73
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As you can see, it's zero.

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So this means that our robot manipulator is in singularity.

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And if you see the rank of our Jacobean, it should be five because these two are linearly dependent.

76
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OK?

77
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As you can see, they are the same, so they are linearly dependent.

78
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So our Jacobean is rank deficient.

79
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So it is in singularity.

80
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OK, now let's try to see what will happen when we reach near this singularity.

81
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OK?

82
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Not in singularity, but we are near the singularity.

83
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OK, let's do that by just changing

84
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its fifth component.

85
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So fifteen point five degree away.

86
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From the singularity case, so we are near the singularity, OK?

87
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Not in a singularity, but near the singularity.

88
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Let's see how this affects to our robot.

89
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Let's first see it Jacobean equals 2p 560 dot

90
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zero cube near singularity.

91
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As you can see now, our robot planters check the Jacobean.

92
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It's feet fourth and six columns which represent Jovens are linearly independent.

93
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OK.

94
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They are not dependent.

95
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No.

96
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They are linearly independent, so we have to have.

97
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Let's check its rank of no j, as you can see its full rank.

98
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So it's not.

99
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It has inverse so determinant.

100
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Or however, if the chip determinant of G, as you can see, it is almost zero.

101
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Very, very close to zero.

102
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OK, so what does it mean?

103
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It means that our robot?

104
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Well, not exactly in singularity, but it is near singularity, which we want not only to avoid in

105
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exact singularity, but also we want to avoid the robot manipulator to come near singularity.

106
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OK, let's see why.

107
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Let's see why we award the singularity.

108
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Let's take that we want to achieve.

109
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OK.

110
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And the factor velocity of 0.1 linear velocity zero point one in that directions.

111
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So what should be our joint velocities in order to get that in the vector velocity?

112
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As you know, we have to find inverse of J.

113
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And we have to multiply it with our desire and the factor velocity.

114
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OK.

115
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Let me just or I think it's correct.

116
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OK.

117
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Let's see what's our desired joint velocities that we will get.

118
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These are and the vector elicited.

119
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Now you can see we have a very big problem here, as you can see in order to get zero point one

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velocity meters per second.

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I think velocity in the z direction.

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We had to change.

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The joint velocities have to be nine point eight five two to radians per second, which is very big

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if you make it.

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If you convert it to, um, radians two degrees, excuse me, divided by PI.

126
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You can see that it's approximately six hundred.

127
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OK, six hundred degrees per second.

128
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Can you imagine trying to imagine that joint has to rotate in 600 degrees in a second, which is very,

129
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very fast, and the robot motors cannot achieve that.

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It can damage our robot manipulators motor.

131
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OK?

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And also other hardware related stuff.

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So we want to achieve, however, inexact singularity.

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This will be excuse me.

135
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This will be infinity.

136
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OK.

137
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But as we near the singularity, we will have not infinite, but very big numbers.

138
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OK, so that's why we want to avoid not only the exact singularity, but also the near singularity.

139
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OK.

140
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We can determine.

141
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Let's see its derivative.

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No, our Jacobins derivative, excuse me.

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Not derivative determinant.

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As you can see, the determinant is very small, as we have said earlier, and we can also represent

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this with condition or a number of our Jacobean.

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As you can see, our condition number of Jacobean is very big.

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OK.

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What does this mean?

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This means that when our condition number of the Jacobean is big, this means that our Jakobsson is

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ill conditioned.

151
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OK.

152
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So we are near singularity.

153
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OK, now let's try to get that to to see the singularity is or near singularities by, you know, in

154
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leave mode.

155
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OK, let's do first.

156
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We will use, as you have seen previously, teach method what it will do.

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It will enable.

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US to change the joint of the robot manipulator so we can control it in a leave mode, and we can also

159
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see how it affects our robot manipulators configuration, so we will use callback with callback method.

160
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OK, so we will use inline function R and Q.

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What are these callback function?

162
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OK?

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What does it mean?

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Callback As we change the joints of our robot manipulator, the callback function will be how can I

165
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say it will be arised and we will get a each time our robots model, which is R and all set the joint

166
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values, which are Q OK?

167
00:12:57,680 --> 00:13:04,850
And what we will do, we will do, we will do print these.

168
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We will print condition.

169
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OK.

170
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No condition.

171
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No.

172
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Condition number during these joint variables.

173
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OK.

174
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Jacob, OK, zero Q.

175
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I think it has to work if I didn't do anything wrong.

176
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OK, now as you can see a disposition, the our condition variable is very big.

177
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Now let's try to manipulate this.

178
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I think this is because of that one.

179
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OK, as you can see, this is why we got a very big condition.

180
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No, this was because at first we were in ready mode, which was, you know, and we we were in singularity,

181
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not near single, about exactly the singular.

182
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So that's what our condition number is, that we, as you can see when we changed our cue five, which

183
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avoids which help us to avoid the risk singularities.

184
00:14:16,960 --> 00:14:19,570
So four and six note becomes a long axis.

185
00:14:19,840 --> 00:14:27,160
So instantly our condition number decreased our as you can see when it reaches near singularity, as

186
00:14:27,160 --> 00:14:30,640
you can see, it starts to condition, no starts to increase.

187
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And again, when it avoids the singularity, it starts to decrease.

188
00:14:35,410 --> 00:14:40,850
So what we have said, we have seen that except from this singularity.

189
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Also, our robot becomes singular or becomes near singular when it reaches its alter boundaries.

190
00:14:48,900 --> 00:14:53,620
So if you take your arm or not, take your arm because this is your arm.

191
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If you stretch your arm fully, you will see that at some point your arm will reach singularity and

192
00:15:02,740 --> 00:15:07,560
you will not be able to end to control it or you will control it.

193
00:15:07,570 --> 00:15:14,890
But you cannot stretch it any more because you know your arm is like a robot manipulator and it reaches

194
00:15:14,890 --> 00:15:21,790
its altered bones, or it cannot stretch anymore because of hardware limitations, OK?

195
00:15:22,650 --> 00:15:25,750
And because you have link lengths that are limited.

196
00:15:26,950 --> 00:15:29,890
OK, now let's try to achieve that position.

197
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OK.

198
00:15:31,720 --> 00:15:35,260
Let's try to by just changing it in this way.

199
00:15:35,260 --> 00:15:36,790
OK, like that.

200
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And let's stretch that.

201
00:15:38,470 --> 00:15:46,510
Also like that, as you can see, you can can you see how it switched from the sort to a two to three

202
00:15:46,780 --> 00:15:50,290
to eight to two hundred thirty three?

203
00:15:50,500 --> 00:15:50,930
OK.

204
00:15:50,950 --> 00:15:55,180
This is because we have reached new and we are near singularity.

205
00:15:55,180 --> 00:15:55,570
OK?

206
00:15:55,780 --> 00:16:00,010
Our robot is near singularity, so that is why it is increased that much.

207
00:16:00,250 --> 00:16:04,700
If you change it again, back to like that, you can see that it decrease them.

208
00:16:04,760 --> 00:16:06,940
Just let me just do it always.

209
00:16:07,210 --> 00:16:09,040
As you can see, it's decreased again.

210
00:16:09,460 --> 00:16:10,030
Can you see?

211
00:16:10,160 --> 00:16:10,600
OK.

212
00:16:10,840 --> 00:16:13,640
Let's make it again near singularity.

213
00:16:13,660 --> 00:16:15,730
And you can see it will switch.

214
00:16:15,730 --> 00:16:16,240
No.

215
00:16:16,390 --> 00:16:16,900
OK.

216
00:16:16,930 --> 00:16:18,580
As you can see it switched back.

217
00:16:20,200 --> 00:16:25,830
You can play with that, which is a very useful tool and try to see OK.

218
00:16:25,840 --> 00:16:30,330
As you can see, we have again reached this singularity here by changing five.

219
00:16:31,480 --> 00:16:38,410
OK, by changing this in a leave mode, you can see when the robot will reach near singularity, and

220
00:16:38,410 --> 00:16:41,170
we want to avoid this singularities.

221
00:16:45,190 --> 00:16:57,240
OK, now let me just show one interesting thing also that, OK, now let's try to get the same and the

222
00:16:58,630 --> 00:17:02,830
the what will happen with the same involved Jacobean OK?

223
00:17:02,980 --> 00:17:04,070
Near Singularity.

224
00:17:04,420 --> 00:17:07,360
This is the Jacobean that we get near singularity.

225
00:17:07,370 --> 00:17:09,040
So by using cute and asked.

226
00:17:09,400 --> 00:17:21,080
But now we will try to change the end effectors orientation in y direction by 0.2 radians per second.

227
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OK.

228
00:17:21,550 --> 00:17:27,400
Let's see how much joint velocities we need to do that.

229
00:17:29,050 --> 00:17:30,710
Let's see our kudi.

230
00:17:30,760 --> 00:17:35,860
As you can see now, the values are moderate, not big.

231
00:17:35,860 --> 00:17:37,150
Like here, OK?

232
00:17:37,600 --> 00:17:46,390
So you can see that while in some singularities of the the draw, it is, you know, not achievable

233
00:17:46,390 --> 00:17:54,040
to get some linear velocities, but it is achievable to get or it is possible to get some orientation

234
00:17:54,040 --> 00:17:55,270
configurations, OK.

235
00:17:55,630 --> 00:18:02,620
So this change based on our, you know, singularity configuration, in some cases we can get linear

236
00:18:02,620 --> 00:18:08,440
velocities, but we cannot get orientation velocities or angular velocities.

237
00:18:08,680 --> 00:18:15,010
In some cases, we can get angular velocities, but not linear velocities.

238
00:18:15,580 --> 00:18:19,630
Let's assume a set of generalized joint velocities with unit no.

239
00:18:20,380 --> 00:18:27,610
These general joint velocities lie on the surface of a hyperspace fair in the end dimensional joint

240
00:18:27,610 --> 00:18:28,510
velocity space.

241
00:18:29,110 --> 00:18:34,940
We have seen this equation also, which helps us to determine joint velocities given and the factor

242
00:18:34,950 --> 00:18:35,560
velocity.

243
00:18:36,160 --> 00:18:42,280
If we substitute inside our equation, we will get this new equation, which is the equation of points

244
00:18:42,280 --> 00:18:43,860
on the surface of an El Absorbed.

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This equation is called velocity el absorbed, and it helps us to understand the mechanical ability

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of our orbit in certain directions, namely how much this episode resembles a sphere.

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Then it can achieve arbitrary velocities in these directions.

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Namely, it can manipulate more easily in both directions.

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Let's see that more clearly in MATLAB before jumping into MATLAB, I would like to note that, as you

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can see in this case, we take into consideration only the kinematics of our robot to determine monopole

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ability.

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However, there are other things that affect the multiple abilities, such as mass and inertia of the

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links, and we will take them into account on our future lessons.

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Now, let's come to many probability of our robot manipulator.

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What we will do, we will do first import the model of Puma five 560.

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Excuse me, not like that.

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Puma five six.

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OK, now we will use the command, which is from Peter Caulkers Library.

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This common P5 60, which is model of our robot manipulator, the ellipse.

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So below, see the ellipse in Q and S.

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OK, let's get that Q in this excuse me.

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But OK, let's that Q in this we should have in the history of our robot.

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OK.

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Genius equals the Q all.

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And so Q and this is the position, the joint.

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But I was near singularity.

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So OK, we now try to see our velocity ellipse near a near singularity, and then we will see translational

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velocity.

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OK, not rotational.

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Then we will see also the rotational look.

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Let's see that ellipse, as you can see.

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Let me just make it like that, and let's call x y x label.

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Let me just make x OK, then y label y and Z Label Z.

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OK, now you can see that in X direction or ellipse is not in sphere form.

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OK.

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So even for our robot the manipulator, it is difficult to achieve linear velocities or translational

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velocities in X direction.

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However, let's do that in Y, as you can see now, the velocity ellipse resembles excuse me.

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Yeah, yeah, it resembles sphere more than in X directions, so we can achieve more arbitrary so we

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can manipulate more.

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Easily, our robots manipulator in why?

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Also in that direction, because as you can see in that direction, also our velocity ellipse resembles

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a sphere.

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OK, now let's try to do the same now with not translational, but rotational velocity.

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OK, now this is near singularity and the rotational.

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OK, let me just this one rotational velocity ellipse.

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OK, now let me also again Insert X label, insert y label and insert that label.

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So oh my gosh.

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Well, well, well done.

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OK.

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Z Label X y z.

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Perfect.

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Now let's see in X, as you can see, this is an interesting shape.

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OK.

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This is not resembles sphere.

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OK, so this lets not resemble spheres, so our robot manipulator cannot manipulate or rotate in x direction.

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OK, now the plate in I mean in rotation because this is rotation velocity sphere ellipse.

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Excuse me, in ex-Tottenham hover.

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Let's come to Y.

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As you can see in Y and Z, it resembles, you know, almost perfect sphere.

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OK.

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And so we can have we have grid man applicability in Y and Z directions in terms of rotational velocity.

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OK.

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So as you can see how much v near the sphere, in that amount, we can manipulate our robot easily in

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rotational and translational sense.
