MIT Press Introduction to Autonomous Mobile Robots part 2 pptx
MIT.Press.Introduction.to.Autonomous.Mobile.Robots part 2 pptx
... switches.
Figure 2. 12
The humanoid robot P2 from Honda, Japan. © Honda Motor Corporation.
Specifications:
Maximum speed: 2 km/h
Autonomy: 15 min
Weight: 21 0 kg
Height: 1. 82 m
Leg DOF: 2 x 6
Arm DOF: 2 x 7
Locomotion ... galloping
free fly
N
2
k
1–()!=
k
2=
N
N
2
k
1–()!3! 321 ⋅⋅ 6====
Locomotion 23
Figure 2. 9
The Raibert hopper [28 , 124 ]. Image courtesy of the LegLab...
MIT.Press.Introduction.to.Autonomous.Mobile.Robots Part 10 pptx
... through .
Gs
1
2
s
2
2
+≅
θ
s
1
s
2
atan≅ s
1
1 2 1–
000
121
=
s
2
1–01
2 02
1–01
=
n
n
n
n
x
p
y
p
,()
I
x
p
y
p
,() y
p
m
1
x
p
b
1
+=
m
1
b
1
x
p
y
p
,()
168 Chapter 4
2. Define the ... kernel operators are
commonly used to approximate the behavior of the Canny edge detector. One such early
operator was developed by Roberts in 1965 [29 ]. He used two 2 x 2 masks...
MIT.Press.Introduction.to.Autonomous.Mobile.Robots part 1 doc
... Links to Mobile Robots 314
Index 317
Autonomous
Mobile Robots
Introduction to
Roland
Illah R.
SIEGWART
NOURBAKHSH
Autonomous Mobile Robots
SIEGWART and NOURBAKHSH
Introduction to
Introduction to ... index.
ISBN 0 -26 2-195 02- X (hc : alk. paper)
1. Mobile robots. 2. Autonomous robots. I. Nourbakhsh, Illah Reza, 1970– . II. Title. III. Series.
TJ211.41...
MIT.Press.Introduction.to.Autonomous.Mobile.Robots Part 3 pdf
... provide
Figure 2. 18
Genghis, one of the most famous walking robots from MIT, uses hobby servomotors as its actuators
(http://www.ai .mit. edu/projects/genghis). © MIT AI Lab.
34 Chapter 2
Table 2. 1
Wheel ... order to demonstrate concrete
applications of the concepts discussed above to mobile robots built for real-world activities.
2. 3 .2. 1 Synchro drive
The synchro driv...
MIT.Press.Introduction.to.Autonomous.Mobile.Robots Part 4 potx
... (3.9)
ξ
·
R
+
X
R
+
X
R
x
r1
·
12 ()rϕ
·
1
=
x
r2
·
12 ()rϕ
·
2
=
x
R
·
ξ
·
R
x
R
·
y
R
·
y
R
·
θ
R
·
ξ
·
R
P
ω
1
P
2l
ω
1
r
ϕ
·
1
2l
=
P
ω
2
r
–
ϕ
·
2
2l
=
ξ
I
·
R θ()
1–
rϕ
·
1
2
rϕ
·
2
2
+
0
rϕ
·
1
2l
r– ϕ
·
2
2l
... robot both in order to design appro-
priate mobile robots for tasks and to understand how to create control software for an
instance of mobi...
MIT.Press.Introduction.to.Autonomous.Mobile.Robots Part 7 pot
... 0.
2
=
f
0.
5
=
R
δ d 1=
e 1= δ
d 2= δ
R
0. 02=
R
0.08=
d 1
0
= e 0. 52
6
=
d 11= e 0. 52
4
=
R
0.11
7
=
R
0. 12
9
=
R
f
Perception 121
approach: the pixel-specific circuitry next to every pixel measures and ... between transmitter
and receiver according to
(4.15)
if the transmitter is moving and
(4.16)
if the receiver is moving.
In the case of a reflected wave (figure 4.16b) the...
MIT.Press.Introduction.to.Autonomous.Mobile.Robots Part 8 pot
... navigation
e
s
u
2
v
2
+()xdyd
∫∫
=
e
c
E
x
uE
y
vE
t
++()
2
xdyd
∫∫
=
e
s
λe
c
+
λ
λ
∇
2
u λ E
x
uE
y
vE
t
++()E
x
=
∇
2
v λ E
x
uE
y
vE
t
++()E
y
=
∇
2
∂
2
x
2
δ
∂
2
y
2
δ
+=
Perception 131
•A point in the scene visible to both cameras ... (4.35)
r
21
x
l
f
r
22
y
l
f
r
23
++
z'
l
r
02
+
y
r
f
z'
r
=
r
31
x
l
f
r
32
y
l
f
r
33
++
...
MIT.Press.Introduction.to.Autonomous.Mobile.Robots Part 9 ppsx
... falling within .
µ
0=
σ
1=
2
σ
2 σ
fx
()
1
σ 2
x µ–()
2
2σ
2
–
exp=
-σ
-2 2 3σ-3σ
68 .26 %
95.44%
99. 72%
µ
µ
µ
fx
() x ∞– ∞
fx
()
1
σ 2
x µ–()
2
2σ
2
–
exp=
µ
150 Chapter ... normally distributed vectors
a) Image Space b) Model Space
β
0
=α [rad]
x
1
α
1
r
1
,[]= x
2
α
2
r
2
,[]=
x
1
x
2
–()
T
x
1
x
2
–()α
1
α
2
–()
2
r
1
r
2
–()
2
+...
MIT.Press.Introduction.to.Autonomous.Mobile.Robots Part 11 doc
... robot.
v(t)
ω(t)
θ
X
I
X
I
p
'
p
'
x'
y'
θ'
p
∆s θ∆ 2 +()cos
∆s θ∆ 2 +()sin
∆θ
+
x
y
θ
∆s θ∆ 2 +()cos
∆s θ∆ 2 +()sin
∆θ
+== =
∆
s
∆
θ
;()
Mobile Robot Localization 20 1
One example of such a representation, shown in figure 5. 12, is a 2D representation ... are partic-
ularly appropriate for study given their significant recent successes in enabling mobile
robots...
MIT.Press.Introduction.to.Autonomous.Mobile.Robots Part 12 doc
... 0.50
Figure 5 .21
A geometric office environment (left) and its topological analog (right).
R1
H1
H1
H1 -2
H2
H2-3
H3
R1
R2
H1 -2
H2
H2-3
R2
H3
n
p
r
t
n=()
i
n
22 4 Chapter 5
Note that equation (5 .26 ) is ... n
ti–1+
,()⋅⋅⋅⋅=
Figure 5 .22
A realistic indoor topological environment.
1 1 -2 2 2- 3 3 3-4 4
N
p
1
2
–()1.
0
=
p
2
3
–()0.
2
=
0.6 0.4 1 0.
6
–()0.0
5
⋅+⋅[]
0 .2 0.6 0...
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