okay so if you could just uh where you
were born and where you grew up
so my name's ron daniel i was born in
maidstone kent
england and that's where i grew up
where did you go to school i went to
school in matestone
what was then called the mainstream
technical high school for boys
technical did you learn any uh
engineering while you were there
well yes it was an unusual set of
schools
that only really existed inside kent
which were schools which offered people
engineering education as well as
the more traditional education available
in grammar schools
i wanted to go to university i went to
university at brunell university
which is in london yeah did you study
engineering i studied the electrical
engineering there
and then you went on for your graduate
work my graduate work was at cambridge
king's college
with professor mcfarlane on control
theory
what made you decide to go into control
theory
it's part of the course that interested
me the most i tend to have
a mathematical background and i tend to
have a mathematical approach to things
so that's what appealed to me more than
the other parts of the course
and what got you interested in robotics
oh a long history of interest in robots
and mechanisms
i also was a quite a science fiction fan
as a as a
as a youngster and i'd read a lot of
asimov and so forth irobot and
arthur c clarke so i had an interest in
robots
there's also my name which i found
amusing
given one of the main characters in in
the novels was called our
daniel
what do you consider your first robot or
robot
well that's an interesting question
because
i got into robots via teleoperation not
straight robots so i was actually
interested
in man machine interfaces rather than
autonomous systems and
so after i finished my phd
my main focus my phd was how to
enable designers design control systems
and i was doing my phd
right in the middle of a lot of
excitement going on in the subject
about a new subject called h infinity
which was about
defining control systems in terms of
their robustness properties
it was interesting to look at what
people were trying to do but it seemed
to
factor out the human being from the
design process
and my phd was on trying to
get the human involved with the computer
much more
such that you can actually use the two
sets of skills
from there i looked around at robotics
projects
and the main one that i found that
interested me was
working with the central electricity
generating board
on the main remote maintenance of their
nuclear power stations
so the uk at that time had
two types of power power station we had
the magnox reactors and the advanced gas
cooled reactors
magnox was getting old and there was
a pressure to extend the life of these
reactors and so one of the issues was
how to do remote
maintenance and inspection of these
devices so i
came to oxford to join a research team
with a research fellowship working with
the central electricity generating board
at marchwood which is a lab just outside
southampton
where they did most of their development
work on
the design of remote manipulators and
that's how i got interested
in man-machine interfaces how you
connect up
human beings to machines so you can get
them to cooperate
and did this lead to your interest in
kinematics and
haptics yes it is i i was quite
interested in knowing
or trying to work out how you actually
could
match a human being to
a remote manipulator performing a
complex task
so the early work was mostly associated
with how
how on earth you get
a manipulator down an 8 inch pipe
through 30 feet of concrete
and then reach around and perform
useful tasks so the early work was
mostly about
solving the kinematics problems quickly
given the computing resource that we had
available at that time
so there's a lot of interest in dealing
with things such as singularities
representing manipulability how you go
about computing inverse kinematics
quickly and in real time um
there's also the issue i also became
interested in which was the
that of how do you perform remote tasks
at considerable different distances from
a support point so if you can imagine
you've got something about that diameter
which has gone down 30 feet is anchored
either to the floor of the reactor or to
the ceiling of the reactor
and then it has to reach out 10 15 feet
in an arm which has to unfold itself
and then perform useful tasks and the
sort of useful task we did was
remote drilling replacement of things
called top hats
thermocouples uh replacing bolts holding
the thermal shield
shielding into the concrete
pressure vessel so
the issue was how do you go about
performing these tasks
this the method we developed was
basically
an almost self-contained robot in itself
which had a number of machines like
drills
nut runners all encapsulated inside
something about this by about this
which would be carried at the end of the
arm thrust up against the
say the ceiling the operator would press
a go switch
and the machine would carry out
basically like a machining center
drill a hole insert a nut run a nut on
it and so forth
um so i became interested in how would
you go about performing such
tasks at a remote distance so there were
two issues that were interestingly one
was
the effect of of the robot machine's
compliance on the behavior
such as how can you how can you
accurately position a robot
if it's bouncing around carrying
significant loads subject to machining
forces and so forth
and how do you how can you transmit the
information to the human operator
such that the human gets a feel for
what's going on
because you can't really afford to have
such machines make mistakes
inside a nuclear reactor it's rather
expensive if you break something down
there
so there are issues about reliability
and
transmission of information to the
operator and so forth
what year roughly was this one this was
between
1982 and about
1985.
and so what kind of a video feedback
were you using are we mostly focused on
the
force feedback feedback there were
cameras
also inside the nuclear reactor which
fed
information back but it was not
processed in any way it was just
we looked at using stereo systems and
for example to get a sense of depth
there was very little haptic feedback
from the device
the cgb were interested
in trying to build haptic devices but
the concentration on how people built
these things was
basically they tried to build midi sort
of mini robots
and these robots had um
gears in they had problems with stick
slip
and all sorts of problems associated
with mechanisms of driving
uh something which moves about and
transmits
force to to a human being so that was
the start of when i became interested in
firstly how would you design a mechanism
such that you can transmit forces to a
human being
uh such that the mechanism designed to
match the dynamics of the human hand
so the device that i came up with
was based on a parallel rather than a
serial mechanism and it was direct drive
rather than geared and that
work was done mostly with the uk atomic
energy authority at harwell
and uh the device which we well i
came up with we called the bilateral
stewart platform
or bsp which was a six degree freedom
parallel
mechanism uh direct driven
very very high mechanical bandwidth the
order of you know
high fit for small motion 100 hertz
you could get reasonably large motion at
10 hertz
there's a lot of power inside the system
and
we then try to couple that to a puma 560
which we were modeling as our as our
remote manipulator to see
how well that would perform because
that's when i was working with um quite
closely with aea
that was i would say late 80s
with a guy called patrick fisher who is
my phd student
he worked with aea they had a particular
vision
of trying to productionize the
uh the remote
decommissioning of various nuclear
contaminated
artifacts within within the uk mostly
associated with
the uk atomic energy program in the
1940s and 1950s
sort of things like early early bomb
manufacture and so forth
so this left a number of legacy
components which
have similar legacy components in the us
where you have poorly defined
geometry you have stuff inside
ponds you have machine tools that you
want to take apart
and so we were interested in trying to
work out whether we could use
a nuclear hardened commercial robot
and use that device
as a remote tele operator to perform the
sort of tasks
that would normally be performed by a
human being wearing a
hazard by a hazard suit so if you can
imagine somebody with a big saw
wearing something looking like a
michelin man with air being pumped in
they would be in a radioactive
environment where they could only work
for say one or two hours
trying to cut these things up and put
them inside stainless steel cans
ready for long-term storage so we had a
vision that we could use
nuclear hardened commercial robots such
as the big puma
and we were looking at using things such
as
huge jigsaws and big drills
cutters which would cut through plate
steel very quickly
so they wanted to be at well
we had a vision that we could couple a
human being
to to these machines
so i had a look at the literature on
on human machine interaction and i
became very surprised
at the nature of the literature
and this is another theme which i came
up with
um there are a number of people that i
felt thought the same
in that what people tended to do was
they tended to build a machine
which did something and then they
reported on what it did
so it was the the the the literature of
the time seemed to be full
of look no hands tight papers
and with very little effort going into
the underlying science
behind what they were trying to do
so there was much there wasn't much in
terms of trying to
develop experiments which would
determine this say the science of
manipulation
it was mostly about building something
to perform
a specific task and then you'd report on
how well it performed that task
with little thought about well can you
actually
reduce the problem to a much simpler
problem and ask yourself questions
about the underlying science and the
physics of the system
so that got me interested in the design
of remote manipulators
and one question i felt had not been
answered
was how do you design a good tele
operator and what limited
the performance of tele operators and
that people have been designing these
things
for 50 years they've been sort of trying
to build these devices
and so i asked the people in in the
industry i said well okay
if i gave you two manipulators one
design like this one design like that
how do you determine which one was
better what performance measures would
you use
and they couldn't answer and i then i
asked the question
if i wanted to design a manipulator with
a particular specification
how do you achieve that specification
and how would you determine whether that
specification was achievable
again that could not be answered so
i developed a model of the manipulation
process
in which i removed the manipulator and
just replaced it with an abstract
object performing manipulation then
start ask questions
of that model regarding what would be
the consequences
of achieving the design aim of perfect
transparency for this
device and it quickly became apparent
simply from application of newton's laws
that any perfect manipulator would be
something which would perfectly reflect
momentum
and if you perfectly reflect momentum
from a large manipulator if you've got a
if you imagine what we had we had a
manipulator carrying
a 50 kilogram saw which would then thump
into a piece of steel
now the sort of forces involved with one
of these very large
robots driving into a lump of steel work
extremely large
if you've got perfect force force
feedback for this device
and you're holding onto a very low mass
very high bandwidth device
and it hits something you it just you
just fly off
then if you imagine you've got the
forward coupling
in which the the robot itself is
actually following
your demands the robot itself would
follow your
rebound and itself would rebound and so
what we found was this huge
increase in kinetic energy by virtue of
the fact
that you are actually
faithfully reproducing uh the momentum
that is the force force the changes in
force so the changes of momentum that
the device is experiencing so
that got me thinking about what type of
information that the human being needs
in order to perform manipulation
so it got me interested in the structure
of how people feel
for us and we came up with the notion of
trying to
excite the kinesthetic feel at very low
frequencies as well as
exciting the sense of touch
at high frequencies and cutting out the
middle frequencies
and we chose how much to cut out the
middle frequencies
and the bandwidth of of that of that
notch
by the limits based by the momentum
transfer that you get between the device
and the human being such that you keep
the momentum transfer such that
the velocity of rebound of the human
is going to be the same as the as it
would have been the velocity of rebound
of the device so that you don't get this
increase in kinetic energy by virtue
of the perfect forward coupling of your
position
so the human being would then feel
a much reduced mid-band force
consequence of that is we developed this
strategy
and my my ideal
well we put together a video which was
designed
to put the noses out of joint of certain
people
at this time there was a thing going on
about
uh repair of
of satellites using the uh
the space shuttle and they were training
uh
uh astronauts to put in things called in
orbit
in orbit units or some big sort of boxes
about this big
and i went and visited uh jpl in which
they were
developing this system for inserting
these boxes and they're developing
various
haptic feedback devices for enabling
astronauts
to perform this task and they had these
boxes
about six inches on the side which they
would insert or try to insert inside
site
satellites and they were had this ground
facility for training people and
testing out various ways of doing it and
they're finding it quite difficult
so when i go back to oxford i try to set
up an equivalent task
i don't know if you know about lego
which is a these are tiny little blocks
the difficulty of remote manipulation
increases as you reduce the size of the
object
and the fineness of how you want to
want to control the device so what we
did was he set up a little lego house
remotely and then instead of a highly
trained astronaut
we got the son of one of the academics
who was
i think he was nine at the time
and so he took a video of this gut this
little guy standing on a box to remove
to reach the haptic interface device
and he built a small lego house remotely
using force feedback on a
on a puma 560 arm and he did it stably
and the amount of training that he had
was about 10 minutes
so we managed to get this little child
to perform a very very difficult remote
task
which others were trying to perform
spending much more money than we were
spending
with much more highly trained people i
thought as a good demonstrator what you
could do
if you actually matched the information
flow
that you required to the dynamics and
the information requirements
of the human hand so that got us got
into the area of
basically matching information flow to
the human
so the concept such as impedance
matching
in electrical engineering and here we're
trying to basically do information
matching
by making sure that the information that
was encoded in the momentum
was matched to the dynamics of the hand
and excited the right
receptors in in the fingers at the same
time
so that was one area that i was
interested in the another area i got
interesting was
as i said the control of dynamic of
compliance systems
so we built a rather large compliant
robot to
model how a compliant arm would work
so this was a huge direct drive robot
which was
novel at the time that there were very
few direct drive robots around
and this was a direct drive compliant
arm
that carried out a number of research
i asked a lot of research questions with
this device
one was how do you compensate for
compliance to get accurate positioning
and the mechanism we use was to use an
exoskeleton around the compliant arm
to pick up the kinematic you know have a
rigid kinematics input
in parallel with the compliant
kinematics and use that to derive
the true end point and using that we
were able to demonstrate
really high speed control of this
dynamic arm by
incorporating feedback from strain
sensors on the compliance structure
so we became interested in how do you
use information
ins from strange senses and so forth for
the control of vibration
at the same time there was also an
interest in how do you go about
achieving
high speed computation so you've got to
remember at that time
a really fast computer was 10 megahertz
which seems ridiculous now but um then
10 megahertz was a fast computer
and so we had a very early
multi-processor computer based on
something which people now wouldn't know
what it is is it called a transputer
which was a computer chip
with integrated communications such that
it facilitated
uh processes process of communication
and so we became interested in how you
go about using
parallel processing to compute things
such as inverse kinematics
inverse dynamics and so forth so that
got us interested
in inverse dynamics and so i had a
number of people looking at
implementation of invest dynamics for
vibrating systems compliance systems
so we managed to demonstrate remote
drilling of using compliant arms
that then went on to generate interest
in
where does the information come from
when you perform
remote force reflection tasks
and it turns out that the information
flow is actually
below the capacity of the encoders to
send the information
so if you can imagine that you're
performing a rigid contact task
and you've got these encoders in joints
when you're in contact with a rigid
surface the joints themselves
are not moving sufficiently to excite
the encoders
so the rate of information flow that you
you get from
the joints is
very very small in terms of bits per
second so
the shannon's theorem theory tells us
about how much information you need
in order to perform a task in terms of
the bandwidth and the information rate
and the information rate going on inside
these joints was almost zero
because you're getting the occasional
tick from the encoders
and these encoders were being used in
velocity feedback
systems so you think how on earth is
this working so we
we sort of did some analysis of this and
it turns out that it was
in fact the nonlinear friction of the
internal device
of the drives which was stabilizing
these these
machines when they're in contact with
rigid surfaces
and we demonstrated this by disabling
the velocity feedback and the thing was
still stable
and it turned out that contrary to what
it was said in the literature
the literature said that that
stable contact with rigid surfaces is
very difficult
and stable contact with very soft
surfaces is very easy
what we found was stable contact with
soft surfaces easy
but also stable contact with rigid
surfaces easy what's difficult
are intermediate surfaces where the
information rate is insufficient
to stabilize the device and the device
is not going so slow
such that the non-linear friction
effects are not stabilizing the feedback
loops
so we found that for example steel on
steel was
was stable steel on a
robot on a sponge was stable if you got
something which was sort of
spring it was unstable so
that surprised me in terms it was very
important when you're
designing feedback systems to think
about
the information flow
so that brought me on to the dynamics of
force reflection force control
so how do you go about controlling a
manipulator when it's performing
a contact task now contact task
as i said was considered to be very
difficult if a very stiff surface
and what people reported in the
literature was
very high phase lags in
force controlled servo mechanism so if
you
identified the transfer function say
of a robot forming a rigid task rigid
contact task
you got phase lags reported of
several thousand degrees so which was
humane you know humongous
phase delays in these in these feedback
loops
and people saying well this is terrible
no wonder they're unstable
so i got to thinking where on earth are
these phase delays coming from
and the accepted view in the published
literature at that time is it's coming
from
the compliance in the arm so i did
an estimate of roughly what the arm
would have to look like to give you
this level of time delay in the loop it
turned out
if the time delay was due to the
compliance in the arm
you need an arm which was roughly say
100 meters long made out of one
millimeter
steel wire where you basically twisting
this worm
watching the waves propagate and these
arms were actually made out of monocoque
aluminium
structure and they were you know as
rigid as this table they were like this
there was no way these this this arm had
this type of time delay in its in its
mechanism
so that got us interested in the
mechanism for
of where these time delays come from and
what we found was
that the delay was coming from a
non-minimum phase effect
generated through parallel paths in the
transmission
so if you take a gearbox and you think
about a traditional gearbox
you have a cog which rotates another cog
which rotates against it you transmit
tall
that works fine when the gears are
moving
so on and so forth and keep moving if
the
gears are essentially stable you get
stick slip motion between the teeth
during this stick slip motion there are
now two mechanisms for transmitting
torque
firstly there is the motion of the stick
stick between the teeth
and secondly there is motion by virtue
of the bearings that support
the gear the gear the gear wheels and so
what we we postulated was
that in fact we had two parallel paths
of transmitting torque
one was stick slip through the teeth and
the other was
the mechanisms uh the basically rocking
walking mechanisms between the the uh
gear t
the the gear gear wheels and so we went
back to our identification experiments
and we actually managed for puma arm to
identify where these phase delays were
coming from
and you were getting these sudden three
180 degree phase
changes in the vibe in the in the high
frequency behavior of these arms
and you could identify which particular
gear teeth were sticking
and say oh that one's coming from that
gear gear tooth sticking on that one
and then that one frees up and this one
starts vibrating and we could actually
correlate
all of the phase delays with the
vibrational modes of the internal
structure
of the gearbox or the gear train which
transmitted the torque inside this arm
so that was the postulation so we then
built
a mechanism to try and demonstrate it
experimentally
so we built a gear drive a single gear
drive with a with a
sort of tiny arm on the output
and so we drove it and we got exactly
the same behavior we got this very large
phase delay but this gear device was
special
in that we actually had two motors and
two gearboxes
such that we could drive the output
differentially
so the other way of driving this instead
of the drive just driving the the iron
back and forth to get this huge time
delay
is you could actually drive the gear
boxes differentially
so one moving that way one moving the
other the other way and the output was
the difference in velocity between the
two
such that you never got stick stick in
the gear teeth if you did that
and then drove tried to drive
the little little lever which was the
pretend robot link
it became almost frictionless if you get
hold of it and you could
spin it and just keep on going and if
you did
a dynamic experiment all of the phase
delays disappeared
so experimentally you were able to show
that if you removed the stick slip
behavior
such that you removed the capacity of
the gears to perform these multimodal
vibrational patterns you could get rid
of
all of the phase delay and so we looked
at whether or not
the appropriate way to design arms which
are performing force reflection tasks
would be to drive the arms
differentially
so that started another area of interest
which i became interested in working
with
the joint european tourists in which we
were
they were interested in having this arm
which could go in and do maintenance
once they injected tritium into the
device
i don't know if you're aware of the what
jet is it's a it's the european
uh fusion research reactor which is
about 10 miles down the road from here
which is probably closed down by now but
in those days it was
being prepared to be fired up to do
fusion research using a tokamak and one
of the issues was is going to be
ferociously
radioactive once it had been fired up
and used with tritium
so they were devising ways of
inputting large manipulators with force
reflection
so the same problem as with the cegb so
same pattern again
and they we were looking at ways in
which you could actually
use drives to remove the friction from
the drives so you have
two two problems one is the phase delay
and the other is if you're trying to
use force reflection to a human you
really want to get rid of the friction
in the drivetrain
for the input device there are a number
of ways of doing that
you can either use a very low friction
device use fancy feedback
the third way of doing which is what we
were looking at was using differential
drives such as you get rid of the
friction altogether
so the friction is then just because
you're you're driving in both directions
all the time both ways there's no
columbic friction there's only
there's only the viscous friction left
so it becomes a very linear system
so we looked at that but it didn't come
too much because it turns out that
if you have differential drives you need
very large power flows
between the two drives in order to
control very small signals
so there's an issue in terms of control
authority of differential drives which
needs further investigation
which we never pursued any further but
that was the main practical constraint
on
on on differential drives did you do
much investigation into
neurological proprioception when you
were thinking about these issues
a little bit i worked with
what what a local
medical neurological group
called mary marlborough lodge which
looked at
mechanisms for helping
or assisting particular type of
of disabled people and one area
that that we became interested in was
a particular type of disability in which
people tended to freeze up um
so i had a phd
student who looked at
ways of to enable these people to
communicate
with a computer so what we designed was
in back in about 1990
perhaps a bit earlier than 1990 was a
wrist with a set of accelerometers
a wristband which we put a number of
accelerometers in the wristband
and using this wristband we can compute
where the arm was
so this was a very early form of gesture
control
and what we found was
that these kids that couldn't
perform tasks like touch a computer
could actually perform gestures so if
you said to the
to to the kids so you had a lot of
12-year-olds they really
couldn't use things like a computer you
say to them
could you know one of our favorite ones
was superman
they'd do that and that gesture could
then be used to control things and
another one they liked was stroking a
cat they could stroke a cat
and do superman and use these type of
gestures or hammering
and we could use these as as as ways of
communicating with the computer
via these accelerometers and so we
developed
a a filter which was based on
some predictive control work that other
colleagues were doing which would
from the accelerations estimate what the
excitations were in the muscles driving
the accelerations
so we would back compute the excitations
in the muscles from the accelerations
that we measured
to compute the intentionality of what
the person was trying to communicate
and we demonstrated that that you could
actually
analyze and and communicate with the
computer using these gestures
so it's slightly different to the more
modern stuff in which you're trying to
recognize things like
hand shapes and so forth this was more
to do with working out the
muscle groups that were firing in order
to generate the acceleration
such that we could then predict what it
was that the person was trying to do
and use that as a signal for driving a
computer
i was just curious if if you knew
whether the human arm
whether you're looking at velocities
versus momentums a little bit of both
or in terms of the actual neural
neurological
um we didn't look at it that way
we were in terms of the feedback
control that i did in terms of human
human machine interaction
i was more interested in matching the
dynamics so
the so if you imagine my model of the
human
receptor system was a of a set of band
pass filters
and i was trying to work out where the
information was where the information
was most important
such that i could match maximize the
information flow
whilst matching the momentum transfer so
in theory you'd want all the information
available for
from the environment to be transmitted
to the human being
but if you've got a mismatch in a device
where you have a very large device
being controlled transparently by a very
small hand
you can't transfer all the information
because if you did you'd get this
momentum transfer and if you get
momentum transfer
the human control control system just
can't cope with this
and so you have to be able to keep the
momentum transfer within
within within manageable bounds
whilst transmitting as much information
as possible
so you have to choose where where the
information is going to be
to be flowing whereas the work we did
with the communications was
these people had very uh very very large
number of difficulties in moving
but they we postulated that they could
control
muscle groups but not very well so our
postulate was that there was some
problem with their feedback mechanism
but their feed forward mechanism was
still intact so they could perform
tasks just they couldn't correct them so
what would happen is
they would become very rigid when
performing
a a closed-loop precise task
so if you replace a very precise task
with a very
imprecise task where the motion is
very much open loop then they could
perform these motions and then we could
back compute what the muscle firing
firing pattern should have been based
upon that acceleration
rather than trying to measure the
myoelectric signals directly so we're
interested in knowing whether we could
back compute
these gestures from from from from the
accelerations
so um it would be quite interesting to
we got
got some way of doing that and you work
on the atomic
robot manipulators were you influenced
or not by red whitaker's work and i
designed the systems the robots that
cleaned up through mile island
not really that was a that's a different
type of problem this was very much
driven by the needs of
tightly constrained
static devices where you're not trying
to
navigate through things you're not
trying to find your way through things
um you we assume that most of the
of of the stuff had been mapped out and
we're particularly interested in the
design of the
machine and its impact upon the human
being
as they perform perform the task it's
more about the stability of the human
machine interface
rather than sort of ai type problems of
moving around
i've never really worked much in ai it's
mostly dynamics
mechanism design control theory
information flow
not not not taking the data and
constructing a model of the world and
then moving about in that world
so who who in terms of theory or other
researchers
have been influential on how you pursue
problems
it's difficult to to identify
you know i like i like the work
the main people that influenced what i
was doing people like shannon
and um bowed nyquist so i come from a
controlled theoretic background
and looking at how you how do you incorp
how how do you talk about information
flow within a control context
there's it's a it's a big gap in control
in that people talk about control
systems in terms of dynamics
they rarely talk about control systems
when you're really talking about
information flow
so a simple little paper i produced
many many years ago to demonstrate this
was
one of the things people do when they
design a robot drive system
is they want to design a simple
proportional plus derivative feedback
loop around some motor
and classically you would see uh
sort of folksy ways of doing this in
which
you turn up the uh
velocity feedback until it becomes noisy
then you turn it back a certain amount
and then you wind up the position gain
to a certain amount until you maximize
the performance of of the server
mechanism well
this was nice and folksy and worked well
for uh devices when you in the old
in the 1960s say when the position
devices were things like potentiometers
but you still got the same behavior when
you had encoders
so a question that i posed once was
where does the noise come from in an
encoder and
in fact it's not noise that you get in
an encoder
what happens is that as the velocity of
an encoder
goes to a certain limiting value which
depend upon the amount of feedback
you've got on the system
you actually have a restriction on the
rate of information flow from the
encoder
because you only get information by
virtue of the line crossings
so if you then look at the shannon limit
on what you can achieve
based upon the information flow coming
from the encoder
you find that a lot of the control
predictions of what you can achieve on
this encoder are nonsense
because the bandwidth that the control
mechanism is
is predicting is way beyond the rate
that the information flow can actually
support
and what happens is that when certain
boundaries are passed
the encoder and the control system
interact the dynamics interact
and the system becomes chaotic so if you
try and extract more information out of
a control system
then is available from the sensors there
is a tendency for the system to
inject noise in the form of chaos
that's that's what it that's what the
physical system does and
you start getting these strange cyclic
so you start getting this frequency
doubling and so forth as the device
starts limit cycling between the encoder
lines
if you've got too high again for the
speed that you're going for the
bandwidth you've got available
for the bitrate you've got available
from the encoder then you start getting
all sorts of strange behavior coming out
of it
and it wasn't noise that the people were
experiencing they just had
too much gain for the bit rates that
they had available that is
they're trying to exceed the channel
capacity of the control system
so a control system not only has a
bandwidth if it's got a sensor in it and
it's digital in any
way it's got a channel capacity and very
few people
actually consider the channel capacity
of a control system and they
that that puts a significant constraint
on what's achievable
and i've come across that with many
colleagues that have tried to achieve
impossible things
so for example i had somebody trying to
achieve
velocity control of a turbine set
and they said well i can't get this
thing to work and i said it'll never
work
if you don't have enough bits available
your number of lines on your encoder is
too small
such that the bit rate that you're
getting from your encoder in your
feedback loop
is too small to support the bandwidth
that you're trying to achieve in terms
of your disturbance rejection
so if you're trying to get more
information so in disturbance rejection
you're basically trying to reconstruct
a disturbance using a control system and
reject it
if in reconstructing that disturbance
you need more information than is
available from your sensor system
you're never going to reconstruct it no
matter what fancy control system you use
you just don't have the information rate
to support that that task
and they just don't consider that it's
not part of the control
control theorist lexicon they don't
think about
the channel capacity of their sensor so
any sensor has a channel capacity
and you cannot perform a task a dynamic
task
which requires more information than is
available from your sensor
so if your sensor is providing a
thousand bits per second
and that's it that's your channel
capacity if your
task requires 10 000 bits per second it
doesn't matter what fancy software
you've got you'll never achieve your
task
you don't have the channel capacity
so um
i think what to ask that who have been
some of the people you've collaborated
with over the years
whoa especially in the robotics area oh
you're going back a long way now well
cegb
the atomic energy authority uk robotics
i spent some time developing software
for
companies selling
machine tools using some robotics
work that i did on parallel mechanism
for a company called geodetics
which was which was trying to develop
a parallel mechanism it's basically a
robot for doing machining
um so they were interested in trying to
improve the accuracy and speed and
controllability of those devices
um various people in europe
all over the place isis trying to think
through
any uh any roboticists that we might
recognize
oh well
uh i spent a lot of time working
with ross mccarry who's now in the us in
in australia
who now works on on mining machinery
most of the people i tended to talk to
were within oxford
so the people like andrew blake hewdawn
white
john john leonard day forsyth
margaret fleck mostly mike brady's
students
we used to spend quite a lot of time
chatting to mike um and to
the other guys that came into the lab
quite a few
people have been through oxford and
moved on they've become quite well known
people like hugh don't white for example
um i've got some of my students now come
back to oxford
like paul newman so i remember paul
i supervised his undergraduate project
so uh which was the design it was the
design
of an agv believe it or not
autonomous guided vehicle and as an
undergraduate project what i
got these him to do was to look at
whether we could reverse engineer
these electric screwdrivers to make a
very cheap
uh autonomous vehicle so
just as a as a platform
he had one or two of his own ideas and
he developed that
um a lot of students come through though
remember dave forsyth
i remember john leonard working on agvs
and uh
his his interaction with traction
batteries
concentration the batteries in an agv
these are big batteries and
we used to have these
these autonomous guided vehicles uh in
the basement
of of the jenkin building which is an
old victorian brick building
and we had these the the atv lab was in
the basement with
these huge support beams so you had to
walk along the duck underneath the beams
as you went through
and they had these little vehicles that
trundled around with
little polaroid sensors you you'd walk
in there and these things will be
this thing would be sort of wobbling
around with cameras poking out in all
directions
this is a completely alien world to me
because i remember what i worked on was
sort of big chunky manipulators with
people hanging on to them
and going unstable and sort of hanging
on stirring away with
while trying to perform a drilling task
and they had this vehicle sort of
troubling about the basement there's all
these little things
going like this so lots of ticking
noises with the polaroids going off
and they used to recharge the traction
batteries in the basement which i
thought was a bit dodgy
because there's lots of hydrogen given
off of these big
48 volt batteries but it's stacks of
batteries and bubbling away
inside the basement's not a good idea so
we used to have a little safety
safety arguments about about that
and yeah and how do you go about
unbolting attraction 48 volt
traction battery you don't use a you
don't use
a non-insulated spanner when you do that
you have to ask john about that so these
were students these are these are
i remember those those days and uh i
remember our very early sun network
sun workstations we had these uh
these well they were based on 68 000 and
10's you know
those were the spark stations good god
no no no
no no no no way back
now i remember we put in the very first
thick wire
ethernet local area networking
in our lab that used people used to come
around and look
at this coaxial cable big thick yellow
coaxial cable that diameter
which we we had about we must had about
four computers on this
network which was that was
quite something and we had these sun sun
work stations with 68 000 and 10's in
them
that was 10 megahertz powerful machines
and we had a server
a machine with a server a net a network
a network we had a very early version of
a network system with a server
any uh any funny robot stories
uh i remember when paul newman
discovered the web
yeah i remember the very first when web
the web became available he came in
and said you can do searches and find
things look at this
and he was he was absolutely full of
that
and i remember the arrival of email
on your desk because before we had to go
into the sort of in order to use
email with something you went into the
central vac server room and
logged onto a terminal and then you
could send email
via text well before pine yeah
yeah pine modern yeah i know
i'm saying you know early 80s early 80s
so it was very very early stuff
um i remember when i printed my phd
thesis
i had a very advanced printer because i
had a
double daisy wheel which meant that
not only could i type roman numerals it
could do
mathematical symbols so i think i was
one of the first people to print
my phd thesis using
a printer that could print mathematical
symbols as well as
other as other sort of ordinary letters
like
that was quite a that was quite
something when we did that
this huge things are flying about you
know
big wires in it moving this great big
double daisy wheel around
you've also done some work in a startup
company
yeah yeah yeah um
one of the things that we we've been
through some developments in the
department so my
robot lab was closed down and dismantled
while we built the building
so while that was going on i started to
look at
because mike brady been doing it for so
long i started to look at computer
vision
so i developed my own stereo code
and i looked at ways
of taking stereo
and merging stereo it's ordinary
geometric stereo
with photometric stereo using camel
filter in fact vena felt
so we developed this technology
where we can take
a fairly
low resolution stereo reconstruction of
an object
and merge that with a very high
resolution
normal map generated by photometry and
that gives us a quite a precise
3d small field two and a half d
reconstruction
of objects with very very high
resolution
sort of 100 micron resolution and
i used that to the idea to start a spin
out company
and we now i now have a spin out company
which measures
uh wound volume so you point the 3d
camera at a
i don't know if you know do people want
to know about the gory details of
diabetes one of the issues of diabetes
is that you lose
two things two problems one is you lose
the sense of touch
and secondly you have a restricted blood
flow
so a very common experience
of people with diabetes is that they
might
sort of put that stick their foot on on
a rose thorn
they don't feel it the rose thorn goes
bad uh they
the blood flow is insufficient for it
for the
room to heal and they develop quite a
nasty ulcer
which can be you know quite a large hole
in say your foot or your leg
so it's not uncommon for people to
develop
these large ulcers on their legs and
feet
and an issue with these things is how do
you choose
the dressing regime so in order
to know whether or not you want to put
an expensive dressing on these
on these wounds you need to know whether
they're healing or not and what the rate
of healing is
and the problem is that it's difficult
to tell what the rate of healing is
using an area measurement
so if you have an ordinary camera and
you photograph the wound all that you
can really measure is the area
of the wound so our company sells a
camera 3d camera
you just basically point point click it
processes it
you get a 3d model which you can then
measure things like wound volume
exact area of the wound you can if you
want you can fly in and
inspect things because it's got such
high resolution and from that you can
work out whether or not the
wound is healing and whether or not you
change the way in which you're
treating the wound whether to make it
more aggressive more expensive treatment
and so forth
so that that's what that's they're
selling also it's used for things like
measuring scars and so forth so
it will measure the shape of a scar or
shape of a wrinkle
and did you do this with your students i
did that on my own basically because i
had sort of a small
a small office on the seventh floor of
the lab no no
seventh floor of the apartment no lab so
i had to sort of
basically use paper-bound research
methods for
three or four years while while the lab
was
being rebuilt when was that
oh this was late 90s early 2000s
we now have a brand spanking new lab up
there
and when i came to move my stuff into
the designated space for in the basement
i found that
the lift was too small to get the stuff
in there so
so at that time i was then working with
somebody called marco baccik
on using robots within
wind tunnels so we had this idea of
having a very high performance
force reflecting robot inside a
a what's called a free flow wind turbine
a wind wind tunnel
so if you imagine a big fan which blows
a jet of air
into free space you stick something in
it
we then measure the forces being applied
to
the model under test and then would move
the model under test
such that we could simulate what the
device would do
if it was flying in free space
so we could actually fly
aircraft models or airfoils
inside a wind tunnel dynamically
and it was of interest to people that
were
interested in unstable
flight controlling in the unstable
regime whether your control system is
going to work
and that got onto a subject called
hardware and the loop control
in which basically you're trying to
insert
a mechanism inside
a control loop but part of the device
that you're trying to perform
experiments on
is simulated in software other parts of
the device
are actually the real device so
typically
you would be interested in
looking at the performance of some
horribly non-linear component
which is not well understood which would
be attached to
a large larger object for whose dynamics
you are well understood
so a typical example would be say an
aileron on a rip on a wing
where you want to look at the dynamics
of the aileron but you don't have a
whole aircraft
so you simulate the mass and the
dynamics of the aircraft
and you actually put the small component
in the in the wind tunnel
and you couple it up via actuators and
sensors to your software system which
simulates the large object which you
want to
put in the loop so interested in how you
go about
performing such tasks and getting
reliable predictions from
it so i did that for a number of years
so i'm slowly moving away from robotics
and more towards
control systems and devices
is that one of your main projects today
what i'm working on
today is what i've got the i'm
continuing with my research on
on stereo and what i'm interested in in
stereo
is similar to what i'm interested in in
robotics that is
what determines the ultimate performance
of a stereo system
and the sort of stuff that i do
is basically highly calibrated
um very accurately calibrated stereo
systems so i'm interested in knowing
what
statistical tests you can perform on
algorithms
such that you can reliably predict what
the stereo system is going to do in the
field
so on real images rather than
the test sets that people tend to
produce there are a number of test sets
for
testing stereo algorithms most of the
test images
are not i would say they're
not particularly typical of the sort of
images that i would see
and they would not be typical of natural
images and they have
different statistics so
for example supposing you're interested
in doing
navigation say the stuff that paul
newman does using stereo
then testing a stereo algorithm based
upon many of the
standard image test sets would not tell
you much about how your
stereo algorithm would work in the wild
because the
images from the wild have many
challenging features that are not
present in many of the
of the test set so i've got a phd
student at the moment looking at
how do you generate synthetic images
which have the character statistical
characteristics
that you would wish to test your
algorithm
so you can match your test images to the
specific task that you want your
stereo images to perform because there's
no such thing as the sort of general
image
so and many of many of the stereo images
are
absolutely crazy for my application so
typical stereo image would have
a bright orange teddy bear against a
bright green background
against a bright blue something other
with very clear
surfaces no fuzzy stuff whereas if
you're looking at a real image it tends
to be
various shades of grey lighting is
tends not to be too good you have
problems in
things like repeating texture and all
sorts of issues that
that these these test images tend to
avoid
could you tell us how robotics started
well if you go back into ancient history
and robotics in the uk
there was something called the robotics
initiative
which was run by somebody called peter
davey
via the what was then the
what is now called the epsrc but um that
is the government funding agency for
research within the uk
for for robotics type research
this was
a program where academics were supposed
to work with industry
to develop robotics applications of
interest to industry
and pete davey was in oxford and he had
a project
which was robotic vision-guided
arc welding um
so with a very early
uh i think it was an acer robot
run by a uh i think it was an argent
well
he wasn't some sort of small vax
driving this thing basically was a
computer about this big
with a disk drive in it which was one of
these big sort of
uh like a sort of saucepan upside down
saucepan disk drives
which you had to clunk like that and and
could store something like 10 megs on
one of these disk drives
so a big disk drive for those days and
this uh this was running real-time
control
of um basically uh
an old ccd camera um
very old nowadays which performed all of
the visual processing in a delay line
so you ran the the image stream through
a delay line tap delay line and you
performed
convolution using a tap delay line
because the computers just weren't fast
enough to do convolution
so we had to work out ways of doing
convolution so that was done using
attack delay that
so they were in a research group doing
this art welding
which started in around about 1980 1981
i came to join uh
basically with with that research group
but working with the cgb on in reactor
telemanipulators in 1982 fact uh
february the 1st
1982 i came to oxford as a research
fellow at
edmond hall working with the cegb and
peter davey was running a research group
in in the department of engineering
science
on art welding he spun out a company
called meta machines which then
went on to sell these art welding
machines
to the automotive industry and
before they did that i sat down with
peter dave and talked about
the the future of information
engineering
and software engineering as an
engineering subject
inside oxford and
we sat down and spoke and a strategy
came up
to try and get a chair
in information engineering at oxford
and i was sent off to
on one of my conference trips to visit
somebody called mike brady
at mit to discuss with him whether or
not he'd be interested in coming to
oxford
and that you know this had a lot of
support from the vice chancellors
and so forth so he was approached and
head-hunted for
the the chair of information engineering
and from that nucleus we started the
research group
in robotics so initially it was myself
and mike brady
and they forsythe as his phd student
and two sun workstations so that was the
initial
robotics research group
but it wasn't called a robotics research
group because we didn't have research
groups
in in oxford and that was much
that was not a term used and i had a phd
student at the time
that joined in 1982 called
vaughan mitchell and he said to me why
don't we call ourselves
the robotics research group there
weren't any research groups in the
department so we
we sat down and we designed a little
sort of
letterhead which we could reproduce
in in a laser printer because by then we
had a laser printer
uh one of the earliest laser printers
that i saw so this is this novel that
you could actually have a letterhead
so we do this little drawing of of a
little robot
drawing out the oxford skyline
and we called this called ourselves the
robotics research group
the the the three of us so um and that
was very much frowned upon in the
department because there weren't any
research groups people didn't call
themselves research groups
very modern the idea of having a
research group now everybody has
research groups so everybody's in a
research group
so we were the very first people to
actually call ourselves a research group
so mike
joined the robotics research group and
and created the the nucleus so
he approached number people like andrew
blake who came and joined us
dave murray hugh dark white
uh trying to remember the names of all
the people that come through
uh guy scott came through uh
oh dear me a long time ago now
um that's it this would be 1986 or 85
18 1985 i think when mike arrived
so i've been running the group
by then i've been successful in getting
grant income so it was a bit
embarrassing so what i did was i went to
see the epsrc and say well can i use my
my then to be awarded research grant to
do the control of compliant manipulators
to put some equipment onto
for the lab and so we
they agreed and so i managed to purchase
something called a data cube that if you
know what a data cube was
again very early computing device that
could do
64 multipliers at once
could do convolutions and this thing was
for doing
semi-real-time image processing and data
cube was having a data cube was a big
deal
so i bought a data cube on my project to
look at
control of compliant arms so
this was the early work you early stuff
used by mike
uh dave scythe and so forth whose early
work was on
i think it was color constancy or
something so he was doing this research
and had a number of phd students coming
through then
the the research group just just
exploded
and we got the money for doing um
autonomous guided vehicle control
do i know the names of everybody that
came through
uh who else was there
jim allen he was a research fellow
um oh
too many we had quite a lot of visitors
come through
um
quite quite a few come through we saw
most of the most most
most international researchers came
through then andrew sissman
came um so
he he's more from the light
uh mostly visitors came through so they
didn't come no
not more from mit as faculty members
uh don't recall any from mit coming
through
there's there's a few went off to join
like john leonard
i remember john leonard turning up and
his early work
on something that became known as slam
so this is this this simultaneous
navigation and
so there's sort of he worked with hudan
white on this stuff called slam
so so they had these little agvs that
would build
maps and navigate around i used to have
a little bit of fun at times trying to
compete with them with undergraduates so
for a joke one year i put a little we
have these final
a project that one undergraduate
performs so
for amusement i got one undergraduate to
build a an agv based on a penman plotter
i don't know if you know what a penman
plotter is
yeah it's a little it's like a little it
was a little turtle that could be
programmed using
turtle programming which would move
around
like a little robot and then you could
put a it would
be able to put a pen on the paper and
draw so with this penryn plotter
and we had a visitor from japan called
masayuka inaba
who brought something called a
multi-window vision system with him
which was a video system which could
extract a small window a number of small
windows and perform
computationally intensive processes on a
very
focus component of of the image and so i
got this undergraduate using this
multi-window vision system
with a little cheap camera sitting on
top of this pen and plotter
and i had a tabletop model of the
factory with little
cardboard models of machine tools we had
this penman plotter navigating its way
and doing slam using this this
multi-window vision system as an
undergraduate project
which was quite it's quite good fun to
demonstrate
somebody doing that so we have we we a
lot of our fun projects we tend
tend to do with undergraduates so i had
i had a couple of students come across
from princeton as undergraduate exchange
students
and i got them to build um a little
walking insect
similar to ones that are built in the
states based upon
um radio control servos
but the interesting thing they did was
we got
a line camera and we managed to
using etching techniques from the
physics department
to attach um
fiber optics to this lip to each
single element of this line camera and
these fiber optics were taken off from
the line camera
and poked into small holes drilled into
a ping pong ball
so we had a ping pong ball which with
about
30 receptors receptive fields on it
which acted like a compound eye so
these students built this compound eye
stuck it on top of this little um
little insect and we built a little
micro
controller which would look look at this
compound eye
and make decisions about whether or not
it was safe and this thing was sort of
navigating around the world
uh built completely built by two
undergraduates
very little help from me quite amazing
what they achieved
and we had ways of communicating with it
so you'd send it a signal
and the way it sent back it what it
found was by using b dances
so what we got the insect to do was to
do the bee dance so we had various
wiggles and hopping up and down and
laser raising a leg which would mean
certain things
so we developed a little vocabulary for
this little walking insect
which was similar to what a bee would
use because i'm a beekeeper
so i i have an interest in b so we had
this thing doing b dances
and so it would if you sort of got near
it it would be frightened and
say i'm frightened and scuttle away and
try and find a dark hole to hide in
it had all these various these
performances based upon
what was called subsumption architecture
so we
they had a very very very elementary
version of the subsumption architecture
linked into this little segmented eye in
which this insect could
act autonomously in the world and sort
of tunnel its way around
so that little insect went back off to
princeton when they returned to
princeton
as as final year students so that that
was that was
quite quite good fun so a lot of what we
do is is basically fun with students
so they love building little robot
systems
you mentioned a visitor from japan were
there other visitors from japan
oh we had many people come through all
the time but we didn't have very many
states masayuka inaudible
was somebody that stayed for about three
months we
got the funds for doing that so
and at the time that um the robotics
research group was starting up here what
what else was going on
going on around the united kingdom in
terms of robotics
ah yes that was interesting
yes i remember something called there
was a
thing that mike brady was involved in
called the
the the uk robotics research center
in which the the large the larger
research groups
wrote research proposals to be
considered
as for as a research center of
excellence in robotics research
so i remember edinburgh university
writing one oxford wrote one with
with aa and then we all sat back
with baited breath waiting for the
announcement who'd won this competition
and it turned out to be salford
university
which was surprising so
so so the the uk
center for robotics research was placed
at salford university
in in in a sort of business park in
salford
so we had
we have we must have had one of the
biggest research groups in europe in
oxford
you know a huge huge depth and strength
in computer vision
we had huda white doing autonomous
navigation
mike was doing his agv stuff i was doing
stuff with teddy operation
andrew blake doing computer vision and
resistance
we had many many people here doing all
sorts of things
so then
mike moved off into computer vision and
uh medical
medical imaging later after that so he
sort of left the robotics field and
became more interested in medical
imaging that's after you've sort of
visited france
for a while
and in terms of the relationship between
british robotics
and greater european and american
robotics would you say there was more
influence from
um continental europe or in the united
states
i think most of the influence in oxford
came came came from
the us i think the us are the strongest
influence there's a lot going on in
europe
there's a lot there's a lot of influence
on the vision side in europe
but most most of the robotics
pure sort of stuff that influenced me
was mostly japan and the usa
it wasn't europe there was there was a
small amount of work in the netherlands
which was good but there was most most
of the really good stuff was in
was in the states in japan in robotics
the computer vision is different that's
there's a lot of highly mathematical
computer vision stuff that's come out of
france and so forth
various research like in rio
which was the netherlands group
uh delft university um trying to
remember the names of people
so long ago now like i
i names the tip of my tongue i can't i
can't bring it
to the front at the moment but you know
what it's like i'm getting old
yeah but it's it was
um
leuven university of nirvan
university
ah
they were particularly interested in
describing force control processes so
languages for describing uh assembly
processes and describing force control
algorithms
so no
no no the name's gone
i knew i know very well cincinnati
micron machine
all right yeah but uh
they were mostly influenced by the work
by matt mason i think
so matt mason wrote a very influential
thesis called pushing and shoving which
was
about moving objects around that that
was extremely influential
on the force force control
community so that's why people became
very interested in
force servoing and there was another guy
that
wrote a really good book called control
of machines with friction
who who went and started to spin out
company and
disappeared from it was called armstrong
i think his name was
wrote a really really good
thesis on on machines with with friction
which also was very influential but
again that's the states so matt mason
and armstrong
there's a super cutie another influence
there's lots of people
in the grasping area ken salisbury
yeah i did very little work on grasping
yeah this there's a solitary hand um
i looked at some of the kinematics of
grasping
um i had somebody work with me that did
work in that area but i think
i moved away from i didn't work on on
the control of hands
the only work i did on hands was i i did
some work with
a guy from southampton which which was a
hand called the nightingale hand
and uh
peter kyburd then moved off to canada i
think
so he worked with me on the design of
intelligent hands
so we looked at ways of
linking senses the sense of touch
to strategies for grasp so you would
so the hand would automatically grasp
things if it sensed they were
stipping so that was late 90s such thing
so but i didn't do much work in that
area
what do you see as the biggest problems
that
robotics is facing or the most difficult
challenges
it's difficult for me to say because i
mostly worked in tele operation
and then moved across and i'm now
tending to working harder in the loop
simulation and
i'm now working on on
applying these type of techniques into
mechanisms for use inside jet engines
so i've moved away from robotics and
tended not to work in that area
for a long long time the sort of things
that i found
frustrating about robotics was the lack
of self-discipline regarding
experimental design that is you couldn't
easily
utilize the results that were being
published because
many of the experiments were
irreproducible so
what was frustrating was somebody said i
built this machine and here's its step
response
you know what what what can one tell um
part of the reaction was that i was
involved in
early moves for something called
experimental robotics
which was a series of conferences in
which
you try to concentrate on experiment so
i think experimental design for art
for developing the science of robotics i
think
is a key challenge what experiments do
you need to perform
how do you design an experiment and how
do you ask
questions which are well posed
scientifically
rather than rather than being involved
in
what i described as phenomenological
research in which
you report on what some mechanism did
it i think it requires more thinking
about
what ex what experiments do you need
before let's take what i'm doing at the
moment with stereo
a typical stereo paper
will consist of i've developed this
algorithm
i've tested it on this test set
gee it works well isn't that neat
whereas if you were to say to look at
the physics literature
they don't do that what they would do is
they would describe very carefully
how they would design an experiment to
isolate the issues that they're trying
to investigate so
for example in stereo you might say i'm
interested
in designing an experiment to test the
impact of noise on algorithms
how do you describe this what
experiments do i need to perform
what are my controls what conclusions
can i draw
in what way is this applicable to
other how how extensible is this
how can i extract the maximum amount of
information about
the problem that i'm trying to solve so
i think that a major
challenge to to
um to roboticism experimental design
so i've noticed it with things like
autonomous guided vehicles
you know it's it's very entertaining in
public you know public may be very
interested in seeing
say a video of a vehicle trundling
around
some environment but
how much effort's gone into the design
of the experiments
to test that system and
how how does that stack up against say
what someone would do to design say
the experiments at cern so looking for
the higgs boson
they didn't just sort of glue together
some accelerator turn it on and say what
happened
they spent years thinking about the
design of the experiment any physicist
will spend a lot of effort
designing the experiment what's the
experimental design
even in the softer sciences such as
psychology experimental design is
crucial
so that's i don't know if you agree with
me at all on that
absolutely so so to me
i think that's the big challenge for
robotics the roddick's community used to
is to come up with a science of robotics
so just my little the little thing i did
on teleoperation which was
to look at well okay well let's have an
abstract turkey operator
what does that tell us about the tele
operation system
and that very simple thought experiment
just came up with the idea of
momentum transfer and once you've got
that you can do some experiments
to illustrate this all the work i did on
on phase delays
postulate a mechanism a mechanism that's
causing this
build a piece of experimental equipment
which illustrate this thing
have a hypothesis make some predictions
do an experiment does your experiments
justif just is your hypothesis supported
what what what statistical bounds can
you put on
on the parameters that you're going to
put in
shannon's shan's theory what does that
tell us about control systems
what do you predict will happen if you
try and exceed the bounds
on the channel capacity of this sensor
now how would you perform an experiment
to try that out
what's your advice to young people who
are interested in a
career in robotics
um be prepared to go and visit a number
of places
and be prepared to work in a number of
labs i think one of the mistakes i made
was i stayed in oxford for too long
i think didn't get enough experience of
other people's working other people's
labs
so if you're interested in robots
go go find some really neat projects
going on and be prepared to move to go
and
work in those projects i think so don't
don't sort of
sit at home and so it's quite easy to
stay
stay safe exactly in the uk so if you're
a uk
student you're interested in robotics be
prepared to go to the states study in
the states
go and find where the where the good
people are
great is there anything you'd like to
add not really
i think i've said my bit thank you very
much