TEDGlobal>Geneva
Auke Ijspeert: A robot that runs and swims like a salamander
Filmed:
Readability: 4.8
2,016,271 views
Roboticist Auke Ijspeert designs biorobots, machines modeled after real animals that are capable of handling complex terrain and would appear at home in the pages of a sci-fi novel. The process of creating these robots leads to better automata that can be used for fieldwork, service, and search and rescue. But these robots don't just mimic the natural world -- they help us understand our own biology better, unlocking previously unknown secrets of the spinal cord.
Auke Ijspeert - Roboticist
Auke Ijspeert works at the intersection of robotics, biology and computational neuroscience. Full bio
Auke Ijspeert works at the intersection of robotics, biology and computational neuroscience. Full bio
Double-click the English transcript below to play the video.
00:12
This is Pleurobot.
0
760
1840
00:15
Pleurobot is a robot that we designed
to closely mimic a salamander species
to closely mimic a salamander species
1
3400
3616
00:19
called Pleurodeles waltl.
2
7040
1400
00:21
Pleurobot can walk, as you can see here,
3
9240
2256
00:23
and as you'll see later, it can also swim.
4
11520
2040
00:26
So you might ask,
why did we design this robot?
why did we design this robot?
5
14280
2191
00:28
And in fact, this robot has been designed
as a scientific tool for neuroscience.
as a scientific tool for neuroscience.
6
16960
3762
00:33
Indeed, we designed it
together with neurobiologists
together with neurobiologists
7
21400
2496
00:35
to understand how animals move,
8
23920
1896
00:37
and especially how the spinal cord
controls locomotion.
controls locomotion.
9
25840
2760
00:41
But the more I work in biorobotics,
10
29560
1696
00:43
the more I'm really impressed
by animal locomotion.
by animal locomotion.
11
31280
2381
00:45
If you think of a dolphin swimming
or a cat running or jumping around,
or a cat running or jumping around,
12
33920
4296
00:50
or even us as humans,
13
38240
1576
00:51
when you go jogging or play tennis,
14
39840
1816
00:53
we do amazing things.
15
41680
1240
00:55
And in fact, our nervous system solves
a very, very complex control problem.
a very, very complex control problem.
16
43880
4136
01:00
It has to coordinate
more or less 200 muscles perfectly,
more or less 200 muscles perfectly,
17
48040
3096
01:03
because if the coordination is bad,
we fall over or we do bad locomotion.
we fall over or we do bad locomotion.
18
51160
3680
01:07
And my goal is to understand
how this works.
how this works.
19
55560
2720
01:11
There are four main components
behind animal locomotion.
behind animal locomotion.
20
59160
2840
01:14
The first component is just the body,
21
62800
1936
01:16
and in fact we should never underestimate
22
64760
1976
01:18
to what extent the biomechanics
already simplify locomotion in animals.
already simplify locomotion in animals.
23
66760
3480
01:22
Then you have the spinal cord,
24
70920
1456
01:24
and in the spinal cord you find reflexes,
25
72400
1976
01:26
multiple reflexes that create
a sensorimotor coordination loop
a sensorimotor coordination loop
26
74400
3456
01:29
between neural activity in the spinal cord
and mechanical activity.
and mechanical activity.
27
77880
3480
01:34
A third component
are central pattern generators.
are central pattern generators.
28
82000
2976
01:37
These are very interesting circuits
in the spinal cord of vertebrate animals
in the spinal cord of vertebrate animals
29
85000
3896
01:40
that can generate, by themselves,
30
88920
1616
01:42
very coordinated
rhythmic patterns of activity
rhythmic patterns of activity
31
90560
2736
01:45
while receiving
only very simple input signals.
only very simple input signals.
32
93320
2376
01:47
And these input signals
33
95720
1216
01:48
coming from descending modulation
from higher parts of the brain,
from higher parts of the brain,
34
96960
3056
01:52
like the motor cortex,
the cerebellum, the basal ganglia,
the cerebellum, the basal ganglia,
35
100040
2696
01:54
will all modulate activity
of the spinal cord
of the spinal cord
36
102760
2136
01:56
while we do locomotion.
37
104920
1456
01:58
But what's interesting is to what extent
just a low-level component,
just a low-level component,
38
106400
3216
02:01
the spinal cord, together with the body,
39
109640
1936
02:03
already solve a big part
of the locomotion problem.
of the locomotion problem.
40
111600
2456
02:06
You probably know it by the fact
that you can cut the head off a chicken,
that you can cut the head off a chicken,
41
114080
3422
02:09
it can still run for a while,
42
117532
1381
02:10
showing that just the lower part,
spinal cord and body,
spinal cord and body,
43
118937
2539
02:13
already solve a big part of locomotion.
44
121500
1873
02:15
Now, understanding how this works
is very complex,
is very complex,
45
123397
2459
02:17
because first of all,
46
125880
1296
02:19
recording activity in the spinal cord
is very difficult.
is very difficult.
47
127200
2620
02:21
It's much easier to implant electrodes
in the motor cortex
in the motor cortex
48
129844
2772
02:24
than in the spinal cord,
because it's protected by the vertebrae.
because it's protected by the vertebrae.
49
132640
3056
02:27
Especially in humans, very hard to do.
50
135720
1816
02:29
A second difficulty is that locomotion
is really due to a very complex
is really due to a very complex
51
137560
3776
02:33
and very dynamic interaction
between these four components.
between these four components.
52
141360
3056
02:36
So it's very hard to find out
what's the role of each over time.
what's the role of each over time.
53
144440
3240
02:40
This is where biorobots like Pleurobot
and mathematical models
and mathematical models
54
148880
3736
02:44
can really help.
55
152640
1200
02:47
So what's biorobotics?
56
155480
1256
02:48
Biorobotics is a very active field
of research in robotics
of research in robotics
57
156760
2736
02:51
where people want to
take inspiration from animals
take inspiration from animals
58
159520
2456
02:54
to make robots to go outdoors,
59
162000
2456
02:56
like service robots
or search and rescue robots
or search and rescue robots
60
164480
2656
02:59
or field robots.
61
167160
1200
03:00
And the big goal here
is to take inspiration from animals
is to take inspiration from animals
62
168880
2696
03:03
to make robots that can handle
complex terrain --
complex terrain --
63
171600
2336
03:05
stairs, mountains, forests,
64
173960
1616
03:07
places where robots
still have difficulties
still have difficulties
65
175600
2016
03:09
and where animals
can do a much better job.
can do a much better job.
66
177640
2056
03:11
The robot can be a wonderful
scientific tool as well.
scientific tool as well.
67
179720
2496
03:14
There are some very nice projects
where robots are used,
where robots are used,
68
182240
2620
03:16
like a scientific tool for neuroscience,
for biomechanics or for hydrodynamics.
for biomechanics or for hydrodynamics.
69
184884
3972
03:20
And this is exactly
the purpose of Pleurobot.
the purpose of Pleurobot.
70
188880
2120
03:23
So what we do in my lab
is to collaborate with neurobiologists
is to collaborate with neurobiologists
71
191600
2936
03:26
like Jean-Marie Cabelguen,
a neurobiologist in Bordeaux in France,
a neurobiologist in Bordeaux in France,
72
194560
3216
03:29
and we want to make spinal cord models
and validate them on robots.
and validate them on robots.
73
197800
4040
03:34
And here we want to start simple.
74
202480
1616
03:36
So it's good to start with simple animals
75
204120
1976
03:38
like lampreys, which are
very primitive fish,
very primitive fish,
76
206120
2256
03:40
and then gradually
go toward more complex locomotion,
go toward more complex locomotion,
77
208400
2496
03:42
like in salamanders,
78
210920
1256
03:44
but also in cats and in humans,
79
212200
1496
03:45
in mammals.
80
213720
1200
03:47
And here, a robot becomes
an interesting tool
an interesting tool
81
215880
2376
03:50
to validate our models.
82
218280
1936
03:52
And in fact, for me, Pleurobot
is a kind of dream becoming true.
is a kind of dream becoming true.
83
220240
3016
03:55
Like, more or less 20 years ago
I was already working on a computer
I was already working on a computer
84
223280
3256
03:58
making simulations of lamprey
and salamander locomotion
and salamander locomotion
85
226560
2656
04:01
during my PhD.
86
229240
1536
04:02
But I always knew that my simulations
were just approximations.
were just approximations.
87
230800
3376
04:06
Like, simulating the physics in water
or with mud or with complex ground,
or with mud or with complex ground,
88
234200
3976
04:10
it's very hard to simulate that
properly on a computer.
properly on a computer.
89
238200
2656
04:12
Why not have a real robot
and real physics?
and real physics?
90
240880
2040
04:15
So among all these animals,
one of my favorites is the salamander.
one of my favorites is the salamander.
91
243600
3136
04:18
You might ask why,
and it's because as an amphibian,
and it's because as an amphibian,
92
246760
3456
04:22
it's a really key animal
from an evolutionary point of view.
from an evolutionary point of view.
93
250240
2856
04:25
It makes a wonderful link
between swimming,
between swimming,
94
253120
2056
04:27
as you find it in eels or fish,
95
255200
1896
04:29
and quadruped locomotion,
as you see in mammals, in cats and humans.
as you see in mammals, in cats and humans.
96
257120
4120
04:34
And in fact, the modern salamander
97
262160
1656
04:35
is very close to the first
terrestrial vertebrate,
terrestrial vertebrate,
98
263840
2376
04:38
so it's almost a living fossil,
99
266240
1536
04:39
which gives us access to our ancestor,
100
267800
1936
04:41
the ancestor to all terrestrial tetrapods.
101
269760
2920
04:45
So the salamander swims
102
273240
1376
04:46
by doing what's called
an anguilliform swimming gait,
an anguilliform swimming gait,
103
274640
2496
04:49
so they propagate a nice traveling wave
of muscle activity from head to tail.
of muscle activity from head to tail.
104
277160
3640
04:53
And if you place
the salamander on the ground,
the salamander on the ground,
105
281440
2176
04:55
it switches to what's called
a walking trot gait.
a walking trot gait.
106
283640
2336
04:58
In this case, you have nice
periodic activation of the limbs
periodic activation of the limbs
107
286000
2863
05:00
which are very nicely coordinated
108
288887
1609
05:02
with this standing wave
undulation of the body,
undulation of the body,
109
290520
2656
05:05
and that's exactly the gait
that you are seeing here on Pleurobot.
that you are seeing here on Pleurobot.
110
293200
3656
05:08
Now, one thing which is very surprising
and fascinating in fact
and fascinating in fact
111
296880
2976
05:11
is the fact that all this can be generated
just by the spinal cord and the body.
just by the spinal cord and the body.
112
299880
4136
05:16
So if you take
a decerebrated salamander --
a decerebrated salamander --
113
304040
2000
05:18
it's not so nice
but you remove the head --
but you remove the head --
114
306064
2016
05:20
and if you electrically
stimulate the spinal cord,
stimulate the spinal cord,
115
308104
2672
05:22
at low level of stimulation
this will induce a walking-like gait.
this will induce a walking-like gait.
116
310800
3256
05:26
If you stimulate a bit more,
the gait accelerates.
the gait accelerates.
117
314080
2456
05:28
And at some point, there's a threshold,
118
316560
1896
05:30
and automatically,
the animal switches to swimming.
the animal switches to swimming.
119
318480
2536
05:33
This is amazing.
120
321040
1376
05:34
Just changing the global drive,
121
322440
1496
05:35
as if you are pressing the gas pedal
122
323960
1736
05:37
of descending modulation
to your spinal cord,
to your spinal cord,
123
325720
2136
05:39
makes a complete switch
between two very different gaits.
between two very different gaits.
124
327880
3000
05:44
And in fact, the same
has been observed in cats.
has been observed in cats.
125
332440
2576
05:47
If you stimulate the spinal cord of a cat,
126
335040
2016
05:49
you can switch between
walk, trot and gallop.
walk, trot and gallop.
127
337080
2216
05:51
Or in birds, you can make a bird
switch between walking,
switch between walking,
128
339320
2736
05:54
at a low level of stimulation,
129
342080
1456
05:55
and flapping its wings
at high-level stimulation.
at high-level stimulation.
130
343560
2816
05:58
And this really shows that the spinal cord
131
346400
2016
06:00
is a very sophisticated
locomotion controller.
locomotion controller.
132
348440
2416
06:02
So we studied salamander locomotion
in more detail,
in more detail,
133
350880
2456
06:05
and we had in fact access
to a very nice X-ray video machine
to a very nice X-ray video machine
134
353360
3096
06:08
from Professor Martin Fischer
in Jena University in Germany.
in Jena University in Germany.
135
356480
3576
06:12
And thanks to that,
you really have an amazing machine
you really have an amazing machine
136
360080
2576
06:14
to record all the bone motion
in great detail.
in great detail.
137
362680
2456
06:17
That's what we did.
138
365160
1256
06:18
So we basically figured out
which bones are important for us
which bones are important for us
139
366440
3176
06:21
and collected their motion in 3D.
140
369640
3016
06:24
And what we did is collect
a whole database of motions,
a whole database of motions,
141
372680
2696
06:27
both on ground and in water,
142
375400
1656
06:29
to really collect a whole database
of motor behaviors
of motor behaviors
143
377080
2484
06:31
that a real animal can do.
144
379589
1244
06:32
And then our job as roboticists
was to replicate that in our robot.
was to replicate that in our robot.
145
380858
3150
06:36
So we did a whole optimization process
to find out the right structure,
to find out the right structure,
146
384033
3383
06:39
where to place the motors,
how to connect them together,
how to connect them together,
147
387440
2656
06:42
to be able to replay
these motions as well as possible.
these motions as well as possible.
148
390120
2880
06:45
And this is how Pleurobot came to life.
149
393680
2360
06:49
So let's look at how close
it is to the real animal.
it is to the real animal.
150
397200
2416
06:52
So what you see here
is almost a direct comparison
is almost a direct comparison
151
400960
2496
06:55
between the walking
of the real animal and the Pleurobot.
of the real animal and the Pleurobot.
152
403480
2696
06:58
You can see that we have
almost a one-to-one exact replay
almost a one-to-one exact replay
153
406200
2736
07:00
of the walking gait.
154
408960
1256
07:02
If you go backwards and slowly,
you see it even better.
you see it even better.
155
410240
2600
07:07
But even better, we can do swimming.
156
415520
2376
07:09
So for that we have a dry suit
that we put all over the robot --
that we put all over the robot --
157
417920
3016
07:12
(Laughter)
158
420960
1096
07:14
and then we can go in water
and start replaying the swimming gaits.
and start replaying the swimming gaits.
159
422080
3176
07:17
And here, we were very happy,
because this is difficult to do.
because this is difficult to do.
160
425280
3336
07:20
The physics of interaction are complex.
161
428640
2216
07:22
Our robot is much bigger
than a small animal,
than a small animal,
162
430880
2416
07:25
so we had to do what's called
dynamic scaling of the frequencies
dynamic scaling of the frequencies
163
433320
3056
07:28
to make sure we had
the same interaction physics.
the same interaction physics.
164
436400
2336
07:30
But you see at the end,
we have a very close match,
we have a very close match,
165
438760
2416
07:33
and we were very, very happy with this.
166
441200
1880
07:35
So let's go to the spinal cord.
167
443480
2216
07:37
So here what we did
with Jean-Marie Cabelguen
with Jean-Marie Cabelguen
168
445720
2296
07:40
is model the spinal cord circuits.
169
448040
2240
07:43
And what's interesting
is that the salamander
is that the salamander
170
451040
2136
07:45
has kept a very primitive circuit,
171
453200
1620
07:46
which is very similar
to the one we find in the lamprey,
to the one we find in the lamprey,
172
454844
2652
07:49
this primitive eel-like fish,
173
457520
1976
07:51
and it looks like during evolution,
174
459520
1736
07:53
new neural oscillators
have been added to control the limbs,
have been added to control the limbs,
175
461280
2936
07:56
to do the leg locomotion.
176
464240
1416
07:57
And we know where
these neural oscillators are
these neural oscillators are
177
465680
2176
07:59
but what we did was to make
a mathematical model
a mathematical model
178
467880
2256
08:02
to see how they should be coupled
179
470160
1616
08:03
to allow this transition
between the two very different gaits.
between the two very different gaits.
180
471800
2936
08:06
And we tested that on board of a robot.
181
474760
2560
08:09
And this is how it looks.
182
477680
1200
08:18
So what you see here
is a previous version of Pleurobot
is a previous version of Pleurobot
183
486920
3016
08:21
that's completely controlled
by our spinal cord model
by our spinal cord model
184
489960
3096
08:25
programmed on board of the robot.
185
493080
1600
08:27
And the only thing we do
186
495280
1216
08:28
is send to the robot
through a remote control
through a remote control
187
496520
2176
08:30
the two descending signals
it normally should receive
it normally should receive
188
498720
2496
08:33
from the upper part of the brain.
189
501240
1600
08:35
And what's interesting is,
by playing with these signals,
by playing with these signals,
190
503480
2696
08:38
we can completely control
speed, heading and type of gait.
speed, heading and type of gait.
191
506200
2800
08:41
For instance,
192
509600
1216
08:42
when we stimulate at a low level,
we have the walking gait,
we have the walking gait,
193
510840
3576
08:46
and at some point, if we stimulate a lot,
194
514440
1976
08:48
very rapidly it switches
to the swimming gait.
to the swimming gait.
195
516440
2160
08:51
And finally, we can also
do turning very nicely
do turning very nicely
196
519480
2216
08:53
by just stimulating more one side
of the spinal cord than the other.
of the spinal cord than the other.
197
521720
3520
08:58
And I think it's really beautiful
198
526200
1616
08:59
how nature has distributed control
199
527840
2256
09:02
to really give a lot of responsibility
to the spinal cord
to the spinal cord
200
530120
2856
09:05
so that the upper part of the brain
doesn't need to worry about every muscle.
doesn't need to worry about every muscle.
201
533000
3656
09:08
It just has to worry
about this high-level modulation,
about this high-level modulation,
202
536680
2536
09:11
and it's really the job of the spinal cord
to coordinate all the muscles.
to coordinate all the muscles.
203
539240
3576
09:14
So now let's go to cat locomotion
and the importance of biomechanics.
and the importance of biomechanics.
204
542840
3520
09:19
So this is another project
205
547080
1256
09:20
where we studied cat biomechanics,
206
548360
2416
09:22
and we wanted to see how much
the morphology helps locomotion.
the morphology helps locomotion.
207
550800
3896
09:26
And we found three important
criteria in the properties,
criteria in the properties,
208
554720
3616
09:30
basically, of the limbs.
209
558360
1320
09:32
The first one is that a cat limb
210
560320
1976
09:34
more or less looks
like a pantograph-like structure.
like a pantograph-like structure.
211
562320
2696
09:37
So a pantograph is a mechanical structure
212
565040
2216
09:39
which keeps the upper segment
and the lower segments always parallel.
and the lower segments always parallel.
213
567280
3400
09:43
So a simple geometrical system
that kind of coordinates a bit
that kind of coordinates a bit
214
571600
3096
09:46
the internal movement of the segments.
215
574720
1816
09:48
A second property of cat limbs
is that they are very lightweight.
is that they are very lightweight.
216
576560
3056
09:51
Most of the muscles are in the trunk,
217
579640
1856
09:53
which is a good idea,
because then the limbs have low inertia
because then the limbs have low inertia
218
581520
2896
09:56
and can be moved very rapidly.
219
584440
1776
09:58
The last final important property is this
very elastic behavior of the cat limb,
very elastic behavior of the cat limb,
220
586240
3816
10:02
so to handle impacts and forces.
221
590080
2656
10:04
And this is how we designed Cheetah-Cub.
222
592760
2336
10:07
So let's invite Cheetah-Cub onstage.
223
595120
2200
10:14
So this is Peter Eckert,
who does his PhD on this robot,
who does his PhD on this robot,
224
602160
3656
10:17
and as you see, it's a cute little robot.
225
605840
2056
10:19
It looks a bit like a toy,
226
607920
1256
10:21
but it was really used
as a scientific tool
as a scientific tool
227
609200
2056
10:23
to investigate these properties
of the legs of the cat.
of the legs of the cat.
228
611280
3296
10:26
So you see, it's very compliant,
very lightweight,
very lightweight,
229
614600
2616
10:29
and also very elastic,
230
617240
1256
10:30
so you can easily press it down
and it will not break.
and it will not break.
231
618520
2776
10:33
It will just jump, in fact.
232
621320
1456
10:34
And this very elastic property
is also very important.
is also very important.
233
622800
2880
10:39
And you also see a bit these properties
234
627160
1896
10:41
of these three segments
of the leg as pantograph.
of the leg as pantograph.
235
629080
2400
10:44
Now, what's interesting
is that this quite dynamic gait
is that this quite dynamic gait
236
632280
2776
10:47
is obtained purely in open loop,
237
635080
1896
10:49
meaning no sensors,
no complex feedback loops.
no complex feedback loops.
238
637000
3136
10:52
And that's interesting, because it means
239
640160
2416
10:54
that just the mechanics
already stabilized this quite rapid gait,
already stabilized this quite rapid gait,
240
642600
4016
10:58
and that really good mechanics
already basically simplify locomotion.
already basically simplify locomotion.
241
646640
4176
11:02
To the extent that we can even
disturb a bit locomotion,
disturb a bit locomotion,
242
650840
3296
11:06
as you will see in the next video,
243
654160
1656
11:07
where we can for instance do some exercise
where we have the robot go down a step,
where we have the robot go down a step,
244
655840
3896
11:11
and the robot will not fall over,
245
659760
1616
11:13
which was a surprise for us.
246
661400
1576
11:15
This is a small perturbation.
247
663000
1416
11:16
I was expecting the robot
to immediately fall over,
to immediately fall over,
248
664440
2416
11:18
because there are no sensors,
no fast feedback loop.
no fast feedback loop.
249
666880
2436
11:21
But no, just the mechanics
stabilized the gait,
stabilized the gait,
250
669340
2196
11:23
and the robot doesn't fall over.
251
671560
1576
11:25
Obviously, if you make the step bigger,
and if you have obstacles,
and if you have obstacles,
252
673160
3136
11:28
you need the full control loops
and reflexes and everything.
and reflexes and everything.
253
676320
3656
11:32
But what's important here
is that just for small perturbation,
is that just for small perturbation,
254
680000
2936
11:34
the mechanics are right.
255
682960
1496
11:36
And I think this is
a very important message
a very important message
256
684480
2096
11:38
from biomechanics and robotics
to neuroscience,
to neuroscience,
257
686600
2191
11:40
saying don't underestimate to what extent
the body already helps locomotion.
the body already helps locomotion.
258
688815
4680
11:47
Now, how does this relate
to human locomotion?
to human locomotion?
259
695440
2160
11:49
Clearly, human locomotion is more complex
than cat and salamander locomotion,
than cat and salamander locomotion,
260
697960
3640
11:54
but at the same time, the nervous system
of humans is very similar
of humans is very similar
261
702360
3136
11:57
to that of other vertebrates.
262
705520
1576
11:59
And especially the spinal cord
263
707120
1456
12:00
is also the key controller
for locomotion in humans.
for locomotion in humans.
264
708600
2640
12:03
That's why, if there's a lesion
of the spinal cord,
of the spinal cord,
265
711760
2416
12:06
this has dramatic effects.
266
714200
1496
12:07
The person can become
paraplegic or tetraplegic.
paraplegic or tetraplegic.
267
715720
2776
12:10
This is because the brain
loses this communication
loses this communication
268
718520
2376
12:12
with the spinal cord.
269
720920
1256
12:14
Especially, it loses
this descending modulation
this descending modulation
270
722200
2216
12:16
to initiate and modulate locomotion.
271
724440
1920
12:19
So a big goal of neuroprosthetics
272
727640
1696
12:21
is to be able to reactivate
that communication
that communication
273
729360
2376
12:23
using electrical or chemical stimulations.
274
731760
2440
12:26
And there are several teams
in the world that do exactly that,
in the world that do exactly that,
275
734840
2936
12:29
especially at EPFL.
276
737800
1216
12:31
My colleagues Grégoire Courtine
and Silvestro Micera,
and Silvestro Micera,
277
739040
2496
12:33
with whom I collaborate.
278
741560
1240
12:35
But to do this properly,
it's very important to understand
it's very important to understand
279
743960
3096
12:39
how the spinal cord works,
280
747080
1736
12:40
how it interacts with the body,
281
748840
1696
12:42
and how the brain
communicates with the spinal cord.
communicates with the spinal cord.
282
750560
2480
12:45
This is where the robots
and models that I've presented today
and models that I've presented today
283
753800
2896
12:48
will hopefully play a key role
284
756720
1896
12:50
towards these very important goals.
285
758640
2656
12:53
Thank you.
286
761320
1216
12:54
(Applause)
287
762560
4560
13:04
Bruno Giussani: Auke, I've seen
in your lab other robots
in your lab other robots
288
772100
2636
13:06
that do things like swim in pollution
289
774760
2456
13:09
and measure the pollution while they swim.
290
777240
2456
13:11
But for this one,
291
779720
1216
13:12
you mentioned in your talk,
like a side project,
like a side project,
292
780960
3480
13:17
search and rescue,
293
785640
1216
13:18
and it does have a camera on its nose.
294
786880
2176
13:21
Auke Ijspeert: Absolutely. So the robot --
295
789080
2496
13:23
We have some spin-off projects
296
791600
1429
13:25
where we would like to use the robots
to do search and rescue inspection,
to do search and rescue inspection,
297
793053
3443
13:28
so this robot is now seeing you.
298
796520
1576
13:30
And the big dream is to,
if you have a difficult situation
if you have a difficult situation
299
798120
3176
13:33
like a collapsed building
or a building that is flooded,
or a building that is flooded,
300
801320
3616
13:36
and this is very dangerous
for a rescue team or even rescue dogs,
for a rescue team or even rescue dogs,
301
804960
3336
13:40
why not send in a robot
that can crawl around, swim, walk,
that can crawl around, swim, walk,
302
808320
2896
13:43
with a camera onboard
to do inspection and identify survivors
to do inspection and identify survivors
303
811240
3176
13:46
and possibly create
a communication link with the survivor.
a communication link with the survivor.
304
814440
2776
13:49
BG: Of course, assuming the survivors
don't get scared by the shape of this.
don't get scared by the shape of this.
305
817240
3576
13:52
AI: Yeah, we should probably
change the appearance quite a bit,
change the appearance quite a bit,
306
820840
3296
13:56
because here I guess a survivor
might die of a heart attack
might die of a heart attack
307
824160
2816
13:59
just of being worried
that this would feed on you.
that this would feed on you.
308
827000
2536
14:01
But by changing the appearance
and it making it more robust,
and it making it more robust,
309
829560
2856
14:04
I'm sure we can make
a good tool out of it.
a good tool out of it.
310
832440
2056
14:06
BG: Thank you very much.
Thank you and your team.
Thank you and your team.
311
834520
2286
ABOUT THE SPEAKER
Auke Ijspeert - RoboticistAuke Ijspeert works at the intersection of robotics, biology and computational neuroscience.
Why you should listen
Auke Ijspeert is a professor at the EPFL (the Swiss Federal Institute of Technology at Lausanne), and head of the Biorobotics Laboratory (BioRob). He has a BSc/MSc in Physics from the EPFL and a PhD in artificial intelligence from the University of Edinburgh, with John Hallam and David Willshaw as advisors. He carried out postdocs at IDSIA and EPFL with Jean-Daniel Nicoud and Luca Gambardella, and at the University of Southern California, with Michael Arbib and Stefan Schaal.
Ijspeert is interested in using numerical simulations and robots to get a better understanding of animal locomotion and movement control, and in using inspiration from biology to design novel types of robots and locomotion controllers.
Auke Ijspeert | Speaker | TED.com