uh just uh tell me where you were born
and where you grew up and went to school
sure so i i was born in melbourne
in australia and went to school
initially in melbourne then
moved to the countryside a little town
called castlemaine which is where i went
through high school
and then when it came time for
university had me i went back to
melbourne
and went to university there studied
electrical engineering
and did a master's degree as well and
did you sort of always know you were
going to do electrical engineering or
how did you absolutely i think from
quite a young age i knew i was going to
do something with
electronics so yeah i built i built
radios
uh pull television sets apart things
like that when i was a kid
so it was pretty clear i was going to be
an engineer and probably an electrical
engineer
and yeah i guess when i was at
university then i got interested in
computers
and digital systems what was your
master's
thesis so master's thesis was in the
area of control theory
uh so that's the particular discipline
that
says okay you've got a got a machine
that's got some dynamic characteristics
and it behaves like this but i want it
to behave like something else the
control system uses feedback theory to
make it
do what it is you want it to do so it's
one of the elements of robotics
so yeah after i was interested in that
as an undergraduate
and at the end of my study didn't really
have a job so
i hit up one of my professors and he
took me on as a research assistant
and so i did that i was there for three
years
uh did my master's during that time was
a research assistant for one year
and then he got some money to buy
himself out of teaching
so that brought me into teaching
so for the the last two of those three
years i was i was teaching
uh at the university so i thought
digital systems
and control theory okay
and uh did you stay there for your phd
so that after i finished there i went
and worked for a government research
agency
an organization australia called csiro
commonwealth scientific and industrial
research
organization so it's an applied r d
organization and so i was with them for
a few years before i did my phd so they
kind of sponsored me to do my phd
so i did that part time uh over
three and a three in a bit years uh it
was kind of
aligned with my day job which is it's
kind of brilliant you
get paid to to do your phd and it's a
line with your day job so it was
about as good as it could get and who's
your dissertation advisor
so my advisor was a professor at
melbourne uni called malcolm good
he'd been in melbourne at melbourne
university for quite a while
he spent a period i think he was on
sabbatical
at the ge research labs in schenectady
and he worked there with people like
mark spong
on manipulated dynamics and we came back
from his sabbatical he actually
joined csro for a while so at csiro he
was my boss
and then he went back to the university
and i then
became this student like about a year a
year later
the other thing that's interesting
around this time was that i
spent a year in the us so i done my
masters i was working for this
organization csro i started with them in
84
and in 88 i won a fellowship that
let me go to the university of
pennsylvania to the grasp lab
which is you know still a powerhouse of
robotics research
so when i was there liu paul was there
regina baichi
vijay kumar was there uh but i was
working particularly with lou paul
uh so he was the guy who hosted me there
and i spent
nine months at the grass lab and it was
it was brilliant
and it was at that point i sort of
finished with the grass i came back home
and think yeah i want to do a phd
and and then management said yeah that's
fine
and what was your dissertation before
gone
so my dissertation was on vision based
control so
how do you control what a robot does
using images that come from a camera
which is either watching the robot
or which is on the end of the robot
watching what
what it's doing if before i went to
pennsylvania i was involved
in a project where we're developing some
special purpose hardware
for processing images from cameras
quickly this is a long time ago this is
the 1980s computers were really slow
and they couldn't process images very
quickly so we built this
uh amazing hardware system that images
from a camera would stream through this
thing
and what would come out is what we call
blob features will tell you
where the objects were in the scene how
big they were what their position was
and whatever
and you needed a special gadget like
that if you're able to take data from
the camera
like 25 frames per second get it into a
fairly
concise form which a robot could act on
if you just got millions of pixels
spewing out of a camera
but in those days that was too much for
the computer to deal with but with this
special board
right which would reduce the data rate
give you just the essence of the image
then yeah that could go into robot so i
worked on that project and that
hardware was used in all sorts of things
was used for food processing and traffic
monitoring
i took one of them in my bag when i went
to university pennsylvania
and so there i kind of built my first
vision guided robot system and
yeah it worked that was nice but
performance was not as good as it could
be
so my dissertation was really doing some
very detailed modeling
of the dynamics of a camera this image
processing system and the robot
as a complete system and once i had a
decent model then i could
design a controller which would really
allow the thing to move
very very quickly are you looking at
for the manipulators end yeah so i had a
robot in
in my in my lab one of the unimate
pumas or pumas as americans call them
and yeah that was my that was my lab rat
and i did all my all my work on that and
at the time 80s
early 90s the puma was the workhorse of
of robotics research
and they're all in in rubbish bins now
and people use other kinds of robots but
at the time that was
was the machine some of them are museums
a couple of them really interested in
rubbish skips
so uh what was your first robot
was that your first the first robot that
i
had anything to do it was when i was
still at the university of melbourne
and i can't remember why we did this but
i
bought a really early sort of toy robot
so it was a little
it was a little robot arm it was
probably had a reach like this
like five stepping motors or something
like that and
i wrote program to make it play checkers
or drafts as we would call it and uh so
we played on a board about
this kind of dimension connected up to a
mini computer
so your mini computer is like a rack of
equipment like this yeah so i connected
the
robot up to that and made the individual
joints move
and then put in an algorithm to allow it
to play checkers and i remember for an
open day
uh we had it set up so visitors to the
university they could make their move
i think i had to type into the computer
what their move was and the robot would
come and move its own piece
a person would move there that was that
was that was pretty successful
as an open day demo and that was really
my first
first experience with a with a robot
okay
just gonna pause for a second so we're
back so after you finish your phd did
you go back to csro
yeah i did because i i mean i was still
technically working for that was my that
was my day job
uh so i stayed there for for a while uh
and the day job was in a few different
areas that we were looking at the
application of this high-speed computer
vision technology and we did a food
sorting machine
uh we did a big traffic monitoring
system which is actually still
still running in australia and we'd also
done a bit of work with
in the manufacturing sector
manufacturing in australia has always
been a bit
fraught it's we still have a
just have a manufacturing industry but
every year it gets less and less
it was problematic even even back then
in the in the 90s
and so we work with some indigenous
robot manufacturers and machine tool
manufacturers
trying to you know upskill them that was
probably a long term a losing
proposition
so when they the the chief of my
division said
how would you like to move to brisbane
uh and get involved in mining robotics
yeah just manufacturing robotics
binding robotics how different can it be
uh
i talked about that with my wife and
eventually we decided
we do that so moved to brisbane in 95
and started a small activity in
mining automation and mining robotics
so what was the sort of scope of
industrial robotics in
australia was it pretty much focused on
mining and manufacturing or were there
some other companies and how would you
compare it to the us or japan
i think the fundamental difference i
think between say
the us japan and and is that australia
doesn't have a very we got a small
population and we're relatively small
manufacturing
industry and to service just the local
population it's
it's not really it's not really cost
effective
and the country used to be protected by
tariff barriers but tariff barriers
started to be
torn down in the 80s and 90s and the
local manufacturers just couldn't
compete with
with imports so australia was
one time probably quite self-sufficient
in manufacturing everything
you know textile industry died shoes
footwear
died car industry started a long decline
which is almost played out now so
in some ways it didn't make sense to
to do manufacturing robotics in in
australia
it just didn't didn't fit with the
economic
foundations of the country australia is
interesting in that it's
considered to be a first world country
but the economic underpinnings are
really that of a third world country i
mean it's based on agriculture
and mineral and energy exports that's
what keeps the country afloat
so it was what happened in the 80s and
90s
is to think well okay in japan you know
that
they have particular applications for
robotics in manufacturing
in europe also they do manufacturing uh
the us yeah a lot of manufacturing
there's some military stuff
japan and america had nuclear reactors
and things that needed cleaning up
certain
robots for those applications none of
those things made any sense in australia
i think for a while we're just
slavishly following what everyone else
was doing
i think in the 90s though the penny
dropped and was that we should do
robotics that made sense
in australia so this would be two
two groups quite strong groups grew up
in
the 90s the group at csro where i was we
pushed into uh into mining robotics
and there was the group at the
university of sydney that's so huge
white's group the australian center for
field robotics and they did work
in mining area as well they also did a
lot of work in logistics
and container portal automation and the
like
so you know i think both groups realized
that if you wanted to do robotics in
australia
you had to go after something that was
economically important
and after working in with say the
manufacturing industry which was really
it wasn't very healthy you know they
they
a lot of very small companies weren't
well capitalized weren't really able to
invest in robotics research
probably weren't even able to invest in
robots you could just buy off the shelf
mining everything was completely
different huge turnover
and if you use robots to improve the
productivity
of a process like digging the dirt that
uncovers a coal seam
you improve their productivity by say a
percent you know it's to the company
it's worth millions of dollars a year
it would pay for itself in less than a
year
and so it was just the numbers worked
really well in mining where they didn't
work very well in manufacturing so
it was kind of a push factor and it was
also a pull factor
mining also had a has a safety
consideration as well a number of miners
are killed and injured every year
and that number's much much less than it
ever used to be
but you know it's not zero it's flat
it's plateauing out at some number
bigger than zero and it will be that way
while this human being's involved in the
process
so you know the early big dream of the
mining guys was
to know people underground or in
dangerous places we just put machines
there and that way then you'll get the
get you know the perfect safety record
so uh what would you say were the big
robotics
issues or questions or problems that you
started addressing when you
moved into mining
so the biggest the biggest challenges in
mining
automation is that the world is
continually changing
that's the process of mining right you
start with a with a nice pristine
environment and you want to transform it
so you can get the minerals out so
everything is changing continuously
where you know the paradigm in
manufacturing is
everything's static and arranged
beautifully the robot knows where it is
the robot knows where all the work
pieces are
it knows that it reaches to this cord
that you know it's going to get the
object that it wants and it's going to
put it over here at this coordinate
so very coordinate oriented
and underpinning assumption that the
world is
time invariant in mining it's not like
that you don't exactly know where the
machine is
don't exactly know where is the thing
that it needs to manipulate
uh yet it needs it needs to do that
and what's interesting about that
situation is it actually uses some of
the ideas that my dissertation was about
so
if a robot's got a camera in it for
example and it wants to
reach the widget it doesn't need to know
where it is it doesn't need to know
where the widget is
it just needs to be able to move so that
the distance between the hand and the
widget goes to zero
and so those ideas about the relative
positioning
become important in environments which
are
unorganized and continually changing
and how long did you stay at them
so we started in 95 and that was
just uh two of us and we grew that
activity
over a period of years uh through a lab
with 40 people in it
in 2008 which was when i
i finished at csiro so the certainly the
period between 95
and and 2005
we did a lot of work in in this mining
automation area so we
automated massive excavating machines
you know machines that weigh three four
thousand tons
and are used to uncover coal seams we
automated machines that drive
in the underground tunnel networks of of
metal mines so copper mines gold mines
those sorts of things
and certainly that technology that
technology in particular was licensed to
caterpillar
and that's available as a product they
sell called mine gem
so it was an underground vehicle
navigation system
and that was probably that was kind of
the peak time for
the mining automation work mining
industry is incredibly cyclic
so you go through these continual boom
bust phases
and i think around 2004 or five there
was
yet another bust i think i rode four of
them
boom bust cycles in you know 15 years
it's it's
kind of crazy so around that point then
we figured we needed to
diversify our portfolio and we started
to
get interested in robots for
environmental monitoring so we started
to think about
robots that fly and could you know
monitor
forests and creeks and coastal strips
and also
underwater robots it's a great big
barrier reef
uh off the coast of queensland uh
we're which is young north of where
brisbane is and we thought well that
could be pretty nice we could do
we could build special robots for
tropical reef survey
and then we'd have to go to tropical
reefs
so we started a big activity in uh in
under underwater robotics as well and
both the area robots and the underwater
robots we built
had vision systems in them so they used
vision to work out how they were moving
with respect to the environment
to detect things that they might collide
with and avoid
so there's kind of this thread of vision
going through the work for
you know all that time but was this the
point in which you
sort of branched out into sensor
networks as an interest
okay so the sensor network thing is uh a
thing that quite orthogonal to
everything else that i
that i done before and this started
i think about 2000 around 2004
uh good friend of mine uh daniela roos
and at that time she was at dartmouth
college she later moved to
mit and she gave me
a bunch i think six wireless sensor
network devices
i can't remember exactly what model what
model they were but they were they were
quite primitive but they were they were
kind of cute those little tiny little
things
with a radio and a computer you could
program them and they could talk to each
other
and do and do interesting things and got
interested in what
they could do for environmental
monitoring as well so you could have
robots flying over and looking for a
distance
but you could have these things actually
embedded into into the environment
so we looked at these things and these
were sort of first generation wireless
sensor network nodes and the engineer in
me said these things aren't very well
built
so i had a really good team of uh of
engineers electronics guys software guys
so
we decided we'd build our own a wireless
sensor network device
and there were several several
generations of this thing but we used it
for
you know quite a number of environmental
monitoring
applications and so we put them in we
put them in underwater environments we
put them in rainforests
i put them on sugar farms at one point
we put uh
we put them on animals so we actually
put them in special collars on cows
and monitored where the cows were going
and what they were doing so we actually
built these maps
of space and time and animal behavior so
we could tell when they were resting
and they're ruminating when they were
walking what speed they were walking at
and this provided data that was just
amazed at animal scientists with insider
that we work with because
they had such primitive ways of
acquiring data about what animals
did very labor intensive they built
towers with binoculars and looked down
and make notes on bits of paper
so we just put this thing on animal
download it and they just had the most
gorgeous data
so what kind of things did you learn
about the cows i learned about
how far they they'd walk in a day and
from that then the nutritionist could
work at how many calories they expended
in a day
and therefore how much fodder they
should they should be eating
we learned how they
that what they the animal people call it
how they utilize the pasture but it
basically means where they at
from and they don't eat a pasture
uniformly they eat it very
uniformly how many times they go and
drink
who they hang out with so there was this
great range of
of information that nobody had ever seen
before they get up in the middle of the
night and wander around for a bit
so there was just a wealth of data it
was a streaming out of these devices
that we
that we put onto onto the animals
and we took it one step further and said
and this is this is not our idea this
this is it's a pre-existing idea but we
implemented it
that if the device or the animal knows
where the animal is and you've got
you don't want to you want to stay
within a spatial region
the traditional approach is you put up
fences you can actually program the
device to
um emit an aversive stimulus to the
animal
to stop it crossing a line so the
abusive stimulus
is a noise followed by an electric shock
it sounds pretty terrible but it's it's
not that bad the shock is no worse than
electric fence
the animal quite quickly learns to
associate the sound with an impending
shock
so after three four learning episodes as
soon as i hear the noise then they just
stop going in that direction
so you can keep animals in a in a
spatial region without a physical fence
advantage of that is fences are
expensive to put up
they get washed away in floods and
things like that and in
northern parts of australia there are
huge properties
hundreds of thousands of hectares so
fencing those things is really expensive
so the dream was that this would replace
all
of that and we did experiments working
with some really
some brilliant uh animal behavioralists
within csiro
demonstrated that it worked we could
move the fences around
you could sep you could have different
fences for different animals you could
separate them by sex or by age or
whatever
but it didn't it ultimately didn't go
anywhere and it's
it's probably the project that i'm in
some ways the most fond of and would
love to get back to
uh it's it's almost it's sort of fringy
robotics right you're sort of putting a
device on an animal that makes it behave
in a particular way
it's a control system
that's great so uh for the underwater
wireless networks did you have to use
acoustic
so this was some some joint work again
with daniela roos
and i think by this time she was at mit
and acoustics is the normal way you
solve this problem
but acoustic modems are expensive kind
of energy hungry
and miserably low bandwidth and
because they're emitting an acoustic
signal they interfere with one another
so only one can be talking at a time
so what we want what we just decided to
do or what we decided to investigate
was to put a node on the
on the sea floor and
it had a short-range optical
communications link
and so what would happen is the
underwater vehicle the robot would come
along
you would begin a negotiation with the
node
using optical signaling and then the
device would upload all its data
optically to the robot
and then and then move on so the node
didn't have to actually expend very much
energy it's not sending acoustic pulses
over huge distances
it's sending optical pulses over quite a
short distance so it's very energy
efficient for the node
not so energy efficient for the
submarine because it has to swim around
and visit all the guys but
but it comes home and you can recharge
it so it was an
interesting way of
exploring some sort of asymmetry one guy
uh
takes a big hit on his energy
expenditure but
he comes home and that's actually not
too problematic where the guys are out
in the field for a long time
don't spend very much energy at all so
this was a sort of interesting bunch of
work where you've got
sensor networks which has got its own
research community and
robotics which got its own research
community but actually with these two
types of devices together
you can solve problems in a different
way than using
either one individually so it was a an
interest for quite a few years
looking at how robots and sensor
networks could cooperate
and also in this work with daniella we
looked at how robots could
actually deploy sensor network modes on
the sea floor
pick them up move them reprogram them
and we did some work with
a helicopter with this is with daniella
and with gaurav zakatma at usc
using helicopters to deploy sensor
networks so we dropped nodes out of our
uh a robot helicopter on the ground we
if the network was broken and we could
drop extra nodes in to repair it
so it was an interesting uh
interesting research area quite sort of
different to anything that i
i've done previously in my career so
um can you tell me a little bit about
your sort of overall collaborations with
daniella and guaran
and how you met and came to collaborate
sure
i think i first met daniella i think
at an iser that's the national symposium
in experimental robotics
that bruno siciliano organized
uh on a little island off the coast of
italy uh
that's probably not true actually i
think i met her first
i organized an earlier version of that
meeting which was in 1999 in sydney
and i think daniella came to came to
that
uh but i probably got to know her better
at that the one the one in italy
she introduced me to gorav i think it
was at an iros in
in switzerland that uh the roland sigwa
organized and uh
yeah i think just sort of a good rapport
with with both of them
and uh sort of research interests meshed
so
i've had some of gaurav's students and
some of daniella students have come to
visit me
in australia and i
i don't think there's there hasn't been
much reverse
i don't know if there's been any reverse
traffic but
yeah certainly some of their students
have come to visit me and i've certainly
spent time at each of their labs and
you know collaborated written papers
with them and and their students
have there been any other important
collaborations in your career
a couple of others uh in the area of
this vision-based robot control it's a
topic that's also called visual servoing
surrounding sort of a strange made-up
word but anyway it's stuck
uh the sessions here at this conference
on on visual servo
so i when i was at the grassland i met
uh greg hagar he was a student at
grassland or just
finishing student at grass flat when
when i was there so around
[Music]
1994 or something like that greg
pinged me out of the blue to help
organize the workshop
on visual server and control because
that was an area of interest of his as
well
and a guy that greg knew uh seth
hutchinson
also so uh greg seth and i organized a
couple of
uh equal workshops on visual servering
and then we and we then actually it was
greg
and seth organized a special
issue of ieee transactions
on visual servering and for that they
wrote
a uh a paper
which basically was a a tutorial uh
on the field and so they'd sort of
setting up to write that
and then they invited me to join that
paper
that's probably the most famous paper
that i've ever
is definitely the most famous paper that
i've written it's got a ridiculous
number of cetaceans
so it's hutchinson hager and cork 96
and it's kind of often cited paper
in this area of vision based control or
visual servoing
so so that that was a pretty
productive relationship there i spent a
sabbatical at university of illinois
which is where seth hutchinson's based
uh in 1999 so sort of ten years after
the the grass flab trip i spent some
time working with seth
and with mark spong there and
did a bit more visual servoing stuff and
so another
another quite well-known paper with seth
uh came out of
out of that visit i've got a
a colleague at the australian national
university guy called rob marney
who's a another control system guy also
interested in visual servoing
so i've done quite a bit of work with
rob
he and i have got sort of a mutual
friend francois schulmet
who's from uh an
inria lab at ren in uh in france
and so rob and francois and i have
written
francois and seth and i have written
papers so there's many combinations of
these
uh people active in in vision-based
control
great so how did you end up at
queensland university
so the towards the
end of 2008 uh
i was frustrated for whatever reason
with
uh the place i'd been at uh i think
it was trying to get the timing of this
right but
i think i turned 50 in 2008
and i also got a letter from the
management of csiro saying
congratulations on 25 years
of service and i thought whoa bad set of
numbers
i spent half my life working here and i
published
so i think it was a bit of that it was a
bit of a bit of frustration with the
place and
just the phone call out of the blue one
afternoon from
from somebody i knew a qut saying would
you consider coming so i thought yeah it
sounds a bit interesting so i did an
interview and
offered a position professor that was
pretty cool i think i probably always
figured one day i was going to be
become an academic or professor and but
it took a while to actually
happen so i think that interview was
around 2008
i had a lot of holiday built up and
so i thought i should take the holiday
so 2009
i spent a lot of time on holiday
and that was when i started i started
writing a book
so yeah that happened that happened that
year so spent
three months in paris uh living a
writerly existence just me and my wife
in a little tiny apartment and you know
i started started writing a book
and after that spent a few months in
oxford i wrote some more book
spent most of the next year finishing
the book and
this is the visual control book yeah
so it was i really planned to write a
book but
i sort of thought about it on and off
and i got going i just
it just kind of all came pouring out so
it's a
it's a myth of a book it's about 600
pages but uh
it all needed to be said and yeah i
enjoyed enjoyed the experience of
writing it so yeah it was kind of a long
drawn-out transition between
between csiro and university if i
started there
in january of 2010
and as you're writing that book so what
did you see as sort of the
necessity of writing such a book that
nobody had sort of brought together all
the work and
was your control before or was it that
there wasn't a sort of
overarching theory before it's not a
theory thing
i'm not a very theoretical person i'm
not a very very mathematical person
i probably tend to think a lot in
diagrams
and simple concepts and there are a few
things i thought were missing from
the the set of textbooks that were out
there
one is they all had a fairly fairly
formal and mathematical approach to
to robotics another aspect is that
in terms of what you can understand
treating
robots formally mathematically it's hard
to go much beyond a very simple robot
your robot two joints a robot you know
that moves like this
you know robot a real robot with six
degrees of freedom or more
you just can't write the maths for it uh
it's it's just too horrible
and so one concern of mine was that
these books
kind of lack the insight into real real
robots
because they use mathematics they can't
go to robots to the sort of complexity
of the robots that we actually use
that was one consideration i i
have some open source software that i've
written over a long period of time i
think called the robotics toolbox for
matlab
just came out of my phd work i kind of
tinker with it in bursts
ever since but it allows you to actually
you know solve problems with practical
robots with six joints or eight joints
or whatever and
so i wanted to i wanted to fold that
into into the book somehow so
the book is i'd like to think of it
think of it as a bit of a bit of a
narrative
but it uses the software tools to help
you solve the problems
so it doesn't get too much into the
theory but it allows the reader to
get their hands dirty and solve quite
complicated problems
quite quickly and motivation is that
okay if they
find that interesting and they want to
know how it works then hey there's a lot
of really other good books that they can
go and read
so i didn't want to replicate what the
other books did i wanted to try and get
people
engaged in solving real
realistic problems with minimal pain
getting excited and then wanting to go
and learn learn robotics so
a bit of a sort of inverted approach to
to learning
so that's probably the main thing about
the book so
book doesn't have that many equations in
it but it's got lots of bits of code
so you can open up any particular page
the book and there's some code that says
this is how you make a robot do this so
you can actually type it into matlab and
you know you can replicate the result
and you can plot the
data differently you can change the
parameters change the robot model
it's yeah how we found it different to
be working in an
academic university setting as opposed
to a
company the
there's a couple of really obvious
differences one is one is around
freedom of what you do so at csiro
increasingly the research agenda was set
by other people not by me
so at the university i can do research
really on anything that i want to do
i guess as long as i'm training students
and or generating
uh some publications along the way so
the freedom is a big one
the second one is probably resourcing
and funding at cesaro
the funding was much more
much more lush than it is at the
university so the university you know
it's hard work to get funding you got to
write grant proposals and then wait for
them to come off and
and all of that so university more
freedom
uh less resource the other place more
resource less freedom
so yeah that i think is the fundamental
trade
but you adapted well yeah i think so uh
been successful in some some early early
grants
uh that's got some good colleagues at
the university
so when i went there i sort of dragged a
few other people
in as well so we started start with a
good nucleus and the universe has been
generous in funding us with extra extra
positions so you've got quite a
a good and vibrant lab and that
that's that's a joy to have sort of you
know built this
built this group up can you tell me a
bit about your history with the ieee
robotics and
automation society how you got involved
with it
sure i think i've been a member of the
ieee
for the longest time probably since uh i
was
did my did my phd and you know i come
along to icarus and irs's and
and and those sorts of things you know
subscribe to the transactions the
magazine
probably never paid too much attention
to how the whole
organization worked probably early on
didn't realize all the people are
slaving away to make these things happen
i can't quite remember how i got
involved in the
in the society uh a colleague of mine in
australia alex zielinski
uh and sonic a team i
lent on me a bit to join the ad com i
didn't even know what the adcom was
at that point so i think i i can't
remember what year i
i joined joined the adcom i could
probably work it out
because i get kicked off this year just
2013 so
i've been on it for four years it must
have been 2009
or thereabouts that i that i joined uh
joined the adcom
and that was probably really my first
introduction to what was going on behind
the
the scene so the adcoms like the
parliament of the society so we're
elected by the members
uh there's 18 of us at any one point
it's our job to keep the executive under
control
and yeah so i was then on various kind
of subcommittees
so you got some experience around the
society about how
how it worked and
i try to remember the year that i got
involved in the
in the magazine it was the year before i
went to qut so
it's awesome in 2009 uh i was sort of
they asked me if i'd be interested in
being the editor-in-chief
of of the magazine uh
the reason being that stefano's
tremendous the editor-in-chief of the
magazine
he'd been tapped on the shoulder to
become vice president of member
activities
at the end of 2009 so he had the step
he was doing too much he had he had
dropped something so he decided he would
step down
and there was a search for an editor and
they asked me if i was interested
i think i initially said no and i sort
of thought about it a bit and thought
yeah that could be that could be good i
had been on the editorial board for the
magazine
back in the early 2000s i think i think
i served two terms
as a member of the editorial board or as
an associate editor
is the correct notation for the magazine
so i had some experience with the
magazines had soft spot for the magazine
so yeah it was a
delight to uh work as as editor-in-chief
and uh what were your uh sort of most
accomplished issues
i think there's a few things that i'm
proud of the magazine
one was moving it to electronic delivery
it was something
i think was important to a lot of
members
you know around that time you know
everyone started tablet tablet computers
suddenly appeared right the telematics
is the marvelous
means to read a magazine so it seemed
really timely that we should have the
magazine coming out
electronically so you just download the
file and
browse it on your browser on your tablet
i think the magazine had struggled for a
long time to work out
quite what it was it's not exactly a
trade magazine
it's not exactly a transactions uh
and you know it's
yeah it's it's it's it's a it's a it's
an odd beast
and that was initially i think the
reason why i said
no uh to becoming editor-in-chief and i
sort of thought about it a bit
and thought it really
it really should be a magazine and not a
not a
a transactions light or anything like
that so it was one
push probably all through my editorship
was
i used this word magazine i wanted to
make it more magaziney
and the production people didn't like
the word magazine but i
i i stuck with that and
so my criteria for an article really was
is it if i was a reader would i find
this an interesting article to read
and a lot of the when you say an article
comes in
and most people in this community write
articles like the transaction articles
and they're quite formal they've got a
lot of maths in them
for magazine you don't want that i want
an article that tells a story
that's got quite a lot of good graphics
or pictures
or whatever and i think people in this
community feel uncomfortable writing
like that i my theory is that they use
the formulas and the maths as
some kind of shield to
ward off the blows of the reviewers so
the first thing was to try and convince
people that it's okay to write
an article like that that's readable by
somebody who's not in your narrow
technical area so someone who
got some technical background but you
know not in your specific area
and the other thing then is the
reviewers and the reviewers are also
trained to
you know attack any paper that's that's
presented to them and the most common
criticism from reviewers is always
no contribution and it's something you
really can't refute if
for transactions if the reviewer says
there's no contribution here no novelty
then doesn't get up it doesn't go into
the transactions but
magazine i don't think it matters if
someone else has done it before
that's okay but if someone can tell the
story really well
you know nice words explain it explain
it adequately
it's got some good images i don't care
is it a good story for the reader
so i tried to turn turn around if
reviewers came back and said no
contribution then i'd
say likely that's that's not a valid
criticism for the magazine
it took a while i think for reviewers to
understand what the magazine wanted
to quarrel for authors to understand
what the magazine wanted
i'm not sure we're completely completely
there yet but i think
kind of pushed the thing more towards
being a magazine and less
being transit transactions
the other thing that i thought was
important magazine was columns
so some regular columns uh
in the magazine too just to lighten the
mix a little bit so
there was the ross column which uh steve
cousins wrote
who just said you know what's happening
with the ross project ross was starting
started before i became the
editor-in-chief but it seemed you know
it's a
massive contribution to our community
and you know they should have a soapbox
where they can just
tell us what's going on
and there's a bunch of other regular
columns that i initiated
i probably initiated more columns than
was sensible
because oftentimes not every column ran
every issue because it was just hard to
get the content and
i tried to do an interview piece which
appeared at the back of the magazine and
it did for
probably the first half dozen issues and
then things just started to get away
from me and
that interview fell off and life got
more and more complicated and so
eventually i stepped down as being
before the end of my turn because it was
just just too much going on but
people like the little interview piece
and i like doing it but
uh yeah not sustainable
so uh well apart from the cows and the
96 paper
other ania anything we overlooked that
you look as
as your sort of proud achievements and
robotics or
papers that you've done no i don't
i don't think so i think yeah that the
96 paper is important
uh submits you know some great
collaborations with
with a number of people all around the
world book i'm
i'm pretty i'm pretty delighted with uh
people are reading it and using it and
for teaching and things like that
the open source toolboxes are still
really widely used there's an active
user community and that's a that's a
source of delight
i'm working at the moment on doing an
open
online robotics course seemed like a
good idea when i mentioned
it now i'm up to here in the project and
it's
it's totally massive i i another thing
that i
underestimated and we hope we'll run a
beta at the beginning of next year and
hope to
offer it globally for northern spring
semester
of 2014. that's the plan
so i've been doing lots of lots of
videoing and the rating
i'm working with graphic designers and
learning designers and software support
people
and it's a brilliant project
and i wish i was doing it full-time but
i'm doing it with about 10 percent of my
time in the moment
and it's yeah it's it's hard but uh
there's probably the most exciting thing
i'm doing at the moment
so you've only been at qut for a few
years have you trained some phds in that
time
not quite uh i have at them
so i started with three phd students
two of them and just about to start
writing up so the australian system
phds typically take between three three
to four years
so yeah two of them are just starting to
to write the thesis now and they should
be
graduated the beginning of next year and
i've got some
some more recent phd students starting
so
somewhat i've got something of a
pipeline happening so that's pretty
exciting i've
been what we call an associate
supervisor of phd students before
so because i wasn't an academic i could
never be
you know their principal their principal
advisor
so i've been associated with four or
five
in the past it's not a great number but
now i've got
a couple of my own almost almost done
are they working in field robotics or
what areas are they uh the two are both
both interior robotics
one inkusar is a korean student of mine
and he's working on flying robots the
quadcopters
which are very popular at the moment and
you see some fantastic results with
quadcopters you can see them playing
juggling balls and moving synchronized
to music and whatever
but all of those quadcopters are
operating in environments
they call vicon motion capture
environment so this
big room with all these fancy and
expensive cameras around it
looking at the robot and telling it
where it is very accurately and very
often
a thousand times a second it gets its
position to millimeter accuracy
the real world's not like that so my
project within queue is to say okay can
we put
equivalent sort of sensor capacity onto
the vehicle itself
to kind of turn it inside out put a
vicon light capability
on the robot and so we're using a high
speed camera
on the robot itself not as high speed as
the vicon but still fairly high speed
and using it to maneuver next to fixed
infrastructure
and so vertical pole inspection is the
specific problem we've chosen
so my goal to him was i want to be able
to fly this quadcopter
really close to a pole safely even
though i've got
no skill so the skill is in the
quadcopter he can sense where it is with
respect to the pole
and through the joystick all i simply
say is go up and down
or go left or right the actual hard work
of flying it and keeping it where i want
it to be
is done by the machine so that's one
project
the other project by a student of mine
called steve martin
is concerned with
uh with ground outdoor ground robots
sensing the characteristics of the
ground that it's driving over
so by looking at the power it's exerting
to drive over terrain it can say
something about
its traversability and so he's been
doing some
some mapping and then some path planning
so by driving around it can learn
what's an easy place to drive and what's
a hard place to drive
and if it's got some goals that it's
going to visit then
as it's learning through experiencing
the environment
it can iteratively improve the path that
it takes
to visit these locations using minimum
minimum amount of energy
so that's a that's a nice piece of work
great
and one thing we often ask is uh any uh
spectacular robot failures or funny
stories that you'd like to share
ah there's been probably quite a lot of
robot failures
the one that's probably most mortifying
as a controls guy
is when we're doing some early work on
these big drag line excavators so this
is massive
three and a half thousand ton machine
and
we it rotates on its base and so i was
running the motion control software for
this
and wanting it to to rotate i got a sign
wrong so instead of negative feedback on
this thing it was a positive feedback so
you run the code
the whole thing just started moving uh
really quickly and getting faster and
faster
uh not slower so yeah that was
that was that was spectacular i mean did
what
theoretically it should do but i was on
a very massive machine that i'm sitting
in
right i mean half a dozen other people
are sitting in as well it was
yeah embarrassing oh you eat it
it just took a minute away what's what's
going on
and uh what's your recommendation to
young people who might be interested in
a career in robotics
uh you should do it robotics is gonna be
you know it's gonna be a really big
thing in the future i mean you just
think about it
10 years time are they going to be more
robust to the world or less there's
going to be more
because there's a whole bunch of i think
societal pressures which are going to
cause
more robots to be adopted in society as
demographic shift as a population we get
older there's a whole bunch of labor
still needs to be done but i think
there's going to be less people to do it
there's in agriculture which is a
current interest of mine
you know there's going to be more mouths
to feed on the planet there's less land
because of
urban encroachment climate's changing
all sorts of
all sorts of things i don't think we can
produce food
as much food as we need unless we adopt
technology like robotics
it's going to be you know it's going to
be important in health care
which is something that most societies
just can't afford
the health care that their citizens
expect and i think robots going to play
an important role there
so labor labor-intensive and there are
some jobs that are simple enough robots
could do them now
and as robots get more capable than they
can do more and more
uh sophisticated tasks so there's huge
huge opportunities in in robotics
so yeah get into it
now what do you see as the biggest kind
of theoretical or technical problems
facing robotics over the next
five to ten years or beyond
i think it's probably just picking
picking the right problems to to solve i
think
a lot of the technologies techniques we
want
are already there i think we have
sufficiently good
techniques i think we often don't have
is
is the business the business case
but i think in general
it's not the techniques it's not the
computers they're not what's holding us
back i think we're
probably not focusing on all the right
problems
so it's the comm the problems really
around the commercialization of the
technology
is there anything that we missed
anything you'd like to
add or talk about ah i don't think so
it's been a good chat yeah
we got through a lot very quickly that's
great okay
thank you no worries