An anonymous reader writes "Jim & Louise Gunderson, owners of a Denver-based computer software tool development company, have finally unveiled their autonomous robot, Basil. Basil is completely home built, runs Linux with some instructions in Java, uses a sonar-based 'reification' logic system, and can go get you a beer or a pot of tea. Quoting: 'The plan is this: The Gundersons will ask Basil to go to the bar, request a couple of stouts from the bartender, and then, once they're placed on the titanium tray perched on his head, bring them back to his creators. They haven't told him how to do this — there's no set script in his processors that tells him to roll a certain distance southwest, speak a certain command, then come back. He'll have to figure it all out on his own, using a basic knowledge of bars and beers and so on, reasoning skills and an ability to understand certain parts of the world. When his sonars capture the image of a person, for example, he knows it's a person, not just a nameless object to be avoided. And he knows that, in this case, that person wants a beer.'"
"I recognize a person 69cm away" "I recognize a wooden chair"
Right. Using sonar, the robot is able to determine the composition of the chair.
Given that the robot's speech patterns are not broken at all, and that it speaks in complete sentences, it seems more likely that this is a blinkenlites contraption with a very human person controlling it the whole time.
Differences in the sound reflected in your example are because of the differences in frequency in the originating sound. The sound rangefinding they're using uses one specific frequency and is going to be pretty darn close. Unless they're also using laser rangefinding as well to compare the difference, I don't think there's anyway to distinguish what sort've material an object is made of with just sound.
I don't think there's anyway to distinguish what sort've material an object is made of with just sound.
Modern military-grade sonar can EASILY tell materials just by the sound quality bounceback. So can whales, dolphins, bats and pretty much any creature with ears, including humans.
Try this: Walk into an empty room with sheetrock walls and a wood floor and clap your hands. Now do it in a similar room with a tile floor and wood paneling on the walls. Now an all-concrete cinderblock room. You will notice
Even my human ears can tell the difference between some types of wall coverings based on ambient sound reflections.
Oh, there's a lot more potential for you than that. Humans actually be trained in echolocation [wikipedia.org]. Blind people even pick it up, thinking they're using their face for it, and so it's been called "facial vision".
From reading the article it seems to think every object with 4 feet and a straight back is a wooden chair and all the voices are probably prerecorded. It's not like it can invent new abstract objects on it's own.
Right. Using sonar, the robot is able to determine the composition of the chair.
That's a bit cynical. While it's unlikely this thing is as autonomous as they would like us to believe there may be an explanation for the "detailed" description of the objects. Perhaps it was taught that an object of that height/width is a "wooden chair". And, much as a young child will run around and point at any small animal and say "doggy!" no matter what type of animal it is, anything about that size and shape is recognized as a "wooden chair".
Without more information it's hard to say for sure.
I saw a demonstration of Basil earlier this month at the event mentioned in the article, and the Gundersons explained some of the technology and what they are trying to accomplish.
There is nothing special about the sonar -- it's just a simple low-bitrate input scheme. The Gundersons are focusing on solving the problems of environment perception by focusing on a cognitive model instead of throwing horsepower at interpreting the input in fine detail, as computer vision or perhaps some sort of advanced sonar would. The robot manages an internal model of its environment, and compares the input to its expectations instead of continually trying to reconstruct a scene. Perhaps it distinguishes a chair from a person with clues (a chair doesn't move on its own, for instance).
It seems to me that you have missed (what I believe is) the point. The robot has an initial, object-based, dimensionally-limited/understood model of its environment. If somebody 'moves a chair' when not in the sensory view of the robot, the robot isn't going to get confused, it's just going to process the basics of the space (such as the walls not moving) see that a previous element in that space is now not there, delete that object from its model, add the same object back in its new location. A robot doesn
Listen to the song, Zappa wants to sell his soul to the devil for his titties and beer...
Devil: Listen fool, you've got to prove to me that you're rough Enough to get into hell, That you've got the style enough to get into hell, So start talkin'...
Zappa:Alright, lemme tell ya somethin'
Devil: Alright!
Zappa: I'll prove to you that I'm bad enough to go to hell
Devil: Yeah!
Zappa: Because I have been through it!
Devil: Yeah!
Zappa: I have seen it!
Devil: Yeah!
Zappa: It has happened to me!
Devil: Yeah!
Za
It looks like the sensors are dumb ranging sonars at four heights. Those are very crude sensors; all you get is the range of the nearest solid object in a 30 degree cone. You could probably separate walls, tables, chairs, and humans with that, at least some of the time. It won't ever work very well. People have been fooling with those things since the 1980s. (The usual sonar sensors are left over from Polaroid auto-focus cameras. Very few robotics people have tried to do serious sonar processing, like submarines or bats.) You're just too information-starved. Vision, though...
There's been much more progress in the last five years than most people realize, though. SLAM works now. Vision algorithms actually work. Low-cost inertial devices work. We're starting to see the payoff from the DARPA Grand Challenge, which gave robotics a serious and needed butt-kick.
I will be the first to admit that I don't know that much about the practical application of sonar in situations like this, but abstractly, wouldn't the use of 12 different sonar sensors possibly create a matrix that through some kind of differential process create a sensory model that's more useful than a single sensor or smaller array?
I doubt they have the computing power to do that. You can get a 3D model that way using some of the bleeding edge DSP chips and novel software but it won't give you composition. You would also need higher resolution ultrasonic sensors ones capable of sending out and receiving more complex signals. Multiple frequencies would be better either from on or multiple sensors.
There's been much more progress in the last five years than most people realize, though. SLAM works now. Vision algorithms actually work. Low-cost inertial devices work. We're starting to see the payoff from the DARPA Grand Challenge, which gave robotics a serious and needed butt-kick.
In my humble opinion, the Darpa Grand Challenge, by offering a market to LIDAR makers, made vision-based SLAM a thing of the past and the under-budgeted : This beast [velodyne.com] has 64 laser telemeters on a rotating head. It gives a 100 000 3D points cloud of the environment 10 times per second. A working video slam seems to pale in comparison...
In my humble opinion, the Darpa Grand Challenge, by offering a market to LIDAR makers, made vision-based SLAM a thing of the past and the under-budgeted.
That's what many of us with Grand Challenge entries once thought. Even Sebastian Thrun once thought that. But, in fact, the winning 2005 Stanford "Stanley" vehicle was running mostly on vision. Above 25MPH it was out-driving its LIDAR range. The vision system wasn't doing SLAM, though. It was comparing the road further ahead with the near road. If
Well, I may have a distorted view of the Velodyne's pervasiveness because I am working on a project involving it in my current job but I seem to remember that it became quite popular after Stanley's victory. In 2006 it gave (in an early version) many good results and in 2007 I think I read somewhere that it was used on most of the competing vehicles. Many people I met told me that they saw flash-LIDARs as a promising tech and quite probably as the future of LIDAR sensing but they doubt it will become availa
He'll have to figure it all out on his own, using a basic knowledge of bars and beers and so on, reasoning skills and an ability to understand certain parts of the world.
This strategy seemed to work very well for George W. Bush.
This strategy seemed to work very well for George W. Bush.
You must have a very different definition of 'working well' than I normally use. But Bush's behavior in the White House and Basil's behavior in the bar are eerily similar.
FTFA:
"This is the first time Basil's been out with his brains intact," Louise notes, adding that they've never had him complete complicated tasks in public before. When they brought him out for their recent wedding anniversary party, for example, they turned off his higher-level
At Denning we had a mobile robot security guard. It could roam a factory or warehouse looking for intruders. it had sonar, radar, and other things.
Notifying people of appointments, delivering small objects, and serving drinks is not only possible, it is probably the easiest set of tasks that you can do.
I have a project on-line that allows you to build a basic robot for $500. It has PWM motor control and basic tips on building the base. It uses a PS/2 mouse to do wheel encoders. (cheap) and using a USB A-D/D-A board to control stuff. (I won't give the URL for fear of slashdotting my server.)
So, my two points: 1) It is possible they are doing what they say they can do. 2) Its fairly trivial if you have the time to waste.
I have a project on-line that allows you to build a basic robot for $500. It has PWM motor control and basic tips on building the base. It uses a PS/2 mouse to do wheel encoders. (cheap) and using a USB A-D/D-A board to control stuff.
I am a current user of your software, I found your site when looking for a way to implement wheel encoders for my robot. It has been extremely useful to me.
For the I/O hardware on my robot, I have implemented drivers for both a Pontech SV203 and Arduino Diecimila [arduino.cc] board. I also wrote an encoder driver to use the Linux event interface rather than the ps2 interface so I could use a USB mouse encoder. On top of your software I have written a Player [sourceforge.net] driver to allow me to use the robot within their framework, opening up a massive amount of new high-level functions for the robot.
I just wanted to thank you for making your software freely available, it has helped me transform my robot from nothing to something that can localize, navigate and avoid obstacles. It has done real work sanding my deck and vacuuming my floor, now if I can only get a snowblower attachment going I will be set.
I also wrote an encoder driver to use the Linux event interface rather than the ps2 interface so I could use a USB mouse encoder.
With USB, I could not get the mouse to send events unless and until it wanted too. The PS/2 interface allowed a fairly stable polling system from which I could calculate the interval for PID. We you able to get a stable PID system or, like most of the project, "stable enough" for actual work.
With USB, I could not get the mouse to send events unless and until it wanted too. The PS/2 interface allowed a fairly stable polling system from which I could calculate the interval for PID. We you able to get a stable PID system or, like most of the project, "stable enough" for actual work.
Mostly just "stable enough", I am still working on tuning it since I switched to the Arduino for motor control. The event interface seems to provide the data quickly enough to fit into my loop but I don't know enough about what is going on underneath to know if the mouse is sending events as it gets them. "Close enough for Government work" is the phrase that comes to mind.
Mostly just "stable enough", I am still working on tuning it since I switched to the Arduino for motor control. The event interface seems to provide the data quickly enough to fit into my loop but I don't know enough about what is going on underneath to know if the mouse is sending events as it gets them. "Close enough for Government work" is the phrase that comes to mind.
The problem with the USB mouse interface is that there is no polling mechanism. You get the events when the mouse thinks you want them. Y
THIS is the kind of robot we need! I mean, I had a girlfriend who wouldn't get me a beer and wouldn't have sex, and who started nagging pretty much as soon as the sun came up, so the machine is already ahead on points.
I for one, really like the way they decided to proceed when making this robot. It works by a healthy mix of abstracting and trial and error.
Let's take the wooden chair, that is used as an example in TFA. As far as I understand it, learning about it and using this information for the robot goes like this.
They put the robot in front of the chair and let it use it's sonars on it from different angles and distances. I imagine that in the case of a typical wooden chair with a back it sees four points for the legs and a line for the back. At least I believe that it abstracts it as such. For the first time it will be input to it that the thing it sees is a wooden chair and it knows that all things that have four points about so far from each other in a squared manner and have a line above two of the side points can be regarded as a wooden chair. If it sees another chair made of metal without the back for example, it might consider that to be a wooden chair as well because it's similar enough and in that case the makers correct it's assumption and say it's a metal chair. Sure, it will start to think that all the chairs without the back are metal chairs, but if that's the case in their home, so what, it's right. If it understands anything wrong enough that it fails at its task it can always be corrected and its knowledge about the world as it sees it will increase. Now when performing tasks it can treat the chair as an abstract object, now that it can recognize it. It can memorize where it stands, it can learn to avoid it or push it or whatever, as long as humans correct its assumptions and choices. Now these abstractions could be abstracted even further. The idea is to let it do very simple things and then combine them into larger tasks, much like programmers think about and solve programming problems: If you want to solve a large problem and you don't know how to, you break it into smaller pieces until you get a piece, that is simple enough to be solved. You solve it and see the next piece. Then you combine the solutions to a solution to the bigger problem and you finally end up with the first and biggest problem getting solved. This robot 'learns' the exact opposite way.
It seems to me that the biggest concern in this case is abstracting the objects it 'sees' into such a form, that they take minimal memory but can still be used in the recognition process.
That came out as ranting. I have no knowledge in the subject and have no idea what I'm talking about but that should make this a good enough Slashdot comment.
Congrats on understanding what it takes to make a successful slashdot post.
Commiserations on entirely failing to grok what this robot is all about.
The key principle this robot uses to sense/model it's surroundings is what it's builders are calling "reification", which they've just published a book about. This is a way to bridge the divide between fuzzy (and semantically empty) sensory data and a symbolic (and semantically rich, if you choose to make it so) model of it's environment. The idea is simple (and
Who wants it to take over the world? I can picture it coming in a box, some assembly required, then its first baby steps would be to learn the environment i.e. the household it'll work in: the couch. the fridge, the carbon based unit that will give it a 5 year mission or until the warranty expires, the domestic US beer it will leave in the fridge, and so on.
The couple have got their priorities straight. With a smug rubbing of the hands, 'Now that the refreshments can be brought to us, what shall we work on
Go east, to a place called Klamath. K-l-a-m-a-t-h. Find Vic. V-i-c. Ask for beer. B-e-e-r. *sigh* You are the chosen one. Find the beer. Be our salvation.
When they brought him out for their recent wedding anniversary party, for example, they turned off his higher-level brain and had him dance around by dumbly bouncing from one lady to the next -- the way most guys function on the dance floor.
Was the quip after the EM dash really necessary? Now, I know that most women have experience with outlaw bikers, but there are a lot of decent guys out there. The problem is they're not outlaw bikers.
FAAAAAKKKEE (Score:5, Insightful)
"I recognize a person 69cm away"
"I recognize a wooden chair"
Right. Using sonar, the robot is able to determine the composition of the chair.
Given that the robot's speech patterns are not broken at all, and that it speaks in complete sentences, it seems more likely that this is a blinkenlites contraption with a very human person controlling it the whole time.
Re:FAAAAAKKKEE (Score:5, Insightful)
I won't disagree that it's fake, but I expect the sonar return is qualitatively affected by the type of surface it hits.
Even my human ears can tell the difference between some types of wall coverings based on ambient sound reflections.
In short, I'd want an expert in sonar to call bullshit on this one before I definitively choose sides.
Parent
Re: (Score:2)
NOOOOT FAAAAAKE! (Score:3, Interesting)
Modern military-grade sonar can EASILY tell materials just by the sound quality bounceback. So can whales, dolphins, bats and pretty much any creature with ears, including humans.
Try this: Walk into an empty room with sheetrock walls and a wood floor and clap your hands. Now do it in a similar room with a tile floor and wood paneling on the walls. Now an all-concrete cinderblock room. You will notice
Re: (Score:2)
And dolphins... they can find things under sand with a quick chirp or two.
Re:FAAAAAKKKEE (Score:5, Informative)
Even my human ears can tell the difference between some types of wall coverings based on ambient sound reflections.
Oh, there's a lot more potential for you than that. Humans actually be trained in echolocation [wikipedia.org]. Blind people even pick it up, thinking they're using their face for it, and so it's been called "facial vision".
Parent
Re: (Score:3, Insightful)
From reading the article it seems to think every object with 4 feet and a straight back is a wooden chair and all the voices are probably prerecorded. It's not like it can invent new abstract objects on it's own.
Re: (Score:2)
I've got four feet and a straight back, you insensitive clod!
Re: (Score:3, Insightful)
Right. Using sonar, the robot is able to determine the composition of the chair.
That's a bit cynical. While it's unlikely this thing is as autonomous as they would like us to believe there may be an explanation for the "detailed" description of the objects. Perhaps it was taught that an object of that height/width is a "wooden chair". And, much as a young child will run around and point at any small animal and say "doggy!" no matter what type of animal it is, anything about that size and shape is recognized as a "wooden chair".
Without more information it's hard to say for sure.
Re: (Score:3, Interesting)
I know the people involved. They're not fraudsters.
Re:FAAAAAKKKEE (Score:4, Informative)
I saw a demonstration of Basil earlier this month at the event mentioned in the article, and the Gundersons explained some of the technology and what they are trying to accomplish.
There is nothing special about the sonar -- it's just a simple low-bitrate input scheme. The Gundersons are focusing on solving the problems of environment perception by focusing on a cognitive model instead of throwing horsepower at interpreting the input in fine detail, as computer vision or perhaps some sort of advanced sonar would. The robot manages an internal model of its environment, and compares the input to its expectations instead of continually trying to reconstruct a scene. Perhaps it distinguishes a chair from a person with clues (a chair doesn't move on its own, for instance).
Parent
Re: (Score:3, Interesting)
Bowtie? Nice try. (Score:5, Funny)
Re: (Score:2)
But, I'm a Frank Zappa fan... (Score:5, Funny)
http://www.youtube.com/watch?v=lwb1s1DYnDU [youtube.com]
Is Zappa a Warner artist? (Score:2)
If so, you can kiss that YouTube video goodbye [slashdot.org]!
Re: (Score:2)
Devil: Listen fool, you've got to prove to me that you're rough Enough to get into hell, That you've got the style enough to get into hell, So start talkin'...
Zappa:Alright, lemme tell ya somethin'
Devil: Alright!
Zappa: I'll prove to you that I'm bad enough to go to hell
Devil: Yeah!
Zappa: Because I have been through it!
Devil: Yeah!
Zappa: I have seen it!
Devil: Yeah!
Zappa: It has happened to me!
Devil: Yeah!
Za
Re: (Score:2)
That ain't the version I seem to recall hearing on Dr. Demento decades ago....
EE 83 Ball Model (Score:5, Funny)
Uh-oh (Score:5, Funny)
"...runs Linux with some instructions in Java..."
Uh-oh, they used the J-word. Wait until the Slashdot Religious Order gets their hands on them.
I, for one, (Score:5, Funny)
Sounds exaggerated (Score:5, Insightful)
It looks like the sensors are dumb ranging sonars at four heights. Those are very crude sensors; all you get is the range of the nearest solid object in a 30 degree cone. You could probably separate walls, tables, chairs, and humans with that, at least some of the time. It won't ever work very well. People have been fooling with those things since the 1980s. (The usual sonar sensors are left over from Polaroid auto-focus cameras. Very few robotics people have tried to do serious sonar processing, like submarines or bats.) You're just too information-starved. Vision, though...
There's been much more progress in the last five years than most people realize, though. SLAM works now. Vision algorithms actually work. Low-cost inertial devices work. We're starting to see the payoff from the DARPA Grand Challenge, which gave robotics a serious and needed butt-kick.
Re: (Score:2)
Re: (Score:2)
I doubt they have the computing power to do that. You can get a 3D model that way using some of the bleeding edge DSP chips and novel software but it won't give you composition. You would also need higher resolution ultrasonic sensors ones capable of sending out and receiving more complex signals. Multiple frequencies would be better either from on or multiple sensors.
Re: (Score:3, Informative)
There's been much more progress in the last five years than most people realize, though. SLAM works now. Vision algorithms actually work. Low-cost inertial devices work. We're starting to see the payoff from the DARPA Grand Challenge, which gave robotics a serious and needed butt-kick.
In my humble opinion, the Darpa Grand Challenge, by offering a market to LIDAR makers, made vision-based SLAM a thing of the past and the under-budgeted : This beast [velodyne.com] has 64 laser telemeters on a rotating head. It gives a 100 000 3D points cloud of the environment 10 times per second. A working video slam seems to pale in comparison...
Re: (Score:3, Informative)
In my humble opinion, the Darpa Grand Challenge, by offering a market to LIDAR makers, made vision-based SLAM a thing of the past and the under-budgeted.
That's what many of us with Grand Challenge entries once thought. Even Sebastian Thrun once thought that. But, in fact, the winning 2005 Stanford "Stanley" vehicle was running mostly on vision. Above 25MPH it was out-driving its LIDAR range. The vision system wasn't doing SLAM, though. It was comparing the road further ahead with the near road. If
Re: (Score:2)
Ah, Foreign Policy! (Score:5, Funny)
He'll have to figure it all out on his own, using a basic knowledge of bars and beers and so on, reasoning skills and an ability to understand certain parts of the world.
This strategy seemed to work very well for George W. Bush.
Re: (Score:2)
You must have a very different definition of 'working well' than I normally use. But Bush's behavior in the White House and Basil's behavior in the bar are eerily similar.
FTFA:
Personally ... (Score:2)
... I welcome our beer-toting overlords.
Beer (Score:2, Funny)
Unless it can swim to Europe Hows it going to obey a command to fetch a REAL beer?
European beer Made in USA (Score:2)
Haven't you heard? The largest American brewer IS European now. [google.com]
Denning Mobile Robotics in the '80s (Score:4, Informative)
At Denning we had a mobile robot security guard. It could roam a factory or warehouse looking for intruders. it had sonar, radar, and other things.
Notifying people of appointments, delivering small objects, and serving drinks is not only possible, it is probably the easiest set of tasks that you can do.
I have a project on-line that allows you to build a basic robot for $500. It has PWM motor control and basic tips on building the base. It uses a PS/2 mouse to do wheel encoders. (cheap) and using a USB A-D/D-A board to control stuff. (I won't give the URL for fear of slashdotting my server.)
So, my two points: 1) It is possible they are doing what they say they can do. 2) Its fairly trivial if you have the time to waste.
Re:Denning Mobile Robotics in the '80s (Score:5, Interesting)
I have a project on-line that allows you to build a basic robot for $500. It has PWM motor control and basic tips on building the base. It uses a PS/2 mouse to do wheel encoders. (cheap) and using a USB A-D/D-A board to control stuff.
I am a current user of your software, I found your site when looking for a way to implement wheel encoders for my robot. It has been extremely useful to me.
For the I/O hardware on my robot, I have implemented drivers for both a Pontech SV203 and Arduino Diecimila [arduino.cc] board. I also wrote an encoder driver to use the Linux event interface rather than the ps2 interface so I could use a USB mouse encoder. On top of your software I have written a Player [sourceforge.net] driver to allow me to use the robot within their framework, opening up a massive amount of new high-level functions for the robot.
I just wanted to thank you for making your software freely available, it has helped me transform my robot from nothing to something that can localize, navigate and avoid obstacles. It has done real work sanding my deck and vacuuming my floor, now if I can only get a snowblower attachment going I will be set.
Parent
Re: (Score:2)
I also wrote an encoder driver to use the Linux event interface rather than the ps2 interface so I could use a USB mouse encoder.
With USB, I could not get the mouse to send events unless and until it wanted too. The PS/2 interface allowed a fairly stable polling system from which I could calculate the interval for PID. We you able to get a stable PID system or, like most of the project, "stable enough" for actual work.
Re: (Score:2)
With USB, I could not get the mouse to send events unless and until it wanted too. The PS/2 interface allowed a fairly stable polling system from which I could calculate the interval for PID. We you able to get a stable PID system or, like most of the project, "stable enough" for actual work.
Mostly just "stable enough", I am still working on tuning it since I switched to the Arduino for motor control. The event interface seems to provide the data quickly enough to fit into my loop but I don't know enough about what is going on underneath to know if the mouse is sending events as it gets them. "Close enough for Government work" is the phrase that comes to mind.
Re: (Score:2)
Mostly just "stable enough", I am still working on tuning it since I switched to the Arduino for motor control. The event interface seems to provide the data quickly enough to fit into my loop but I don't know enough about what is going on underneath to know if the mouse is sending events as it gets them. "Close enough for Government work" is the phrase that comes to mind.
The problem with the USB mouse interface is that there is no polling mechanism. You get the events when the mouse thinks you want them. Y
To Hell With Manufacturing... (Score:2, Funny)
THIS is the kind of robot we need! I mean, I had a girlfriend who wouldn't get me a beer and wouldn't have sex, and who started nagging pretty much as soon as the sun came up, so the machine is already ahead on points.
Interesting (Score:5, Interesting)
I for one, really like the way they decided to proceed when making this robot. It works by a healthy mix of abstracting and trial and error.
Let's take the wooden chair, that is used as an example in TFA. As far as I understand it, learning about it and using this information for the robot goes like this.
They put the robot in front of the chair and let it use it's sonars on it from different angles and distances. I imagine that in the case of a typical wooden chair with a back it sees four points for the legs and a line for the back. At least I believe that it abstracts it as such. For the first time it will be input to it that the thing it sees is a wooden chair and it knows that all things that have four points about so far from each other in a squared manner and have a line above two of the side points can be regarded as a wooden chair. If it sees another chair made of metal without the back for example, it might consider that to be a wooden chair as well because it's similar enough and in that case the makers correct it's assumption and say it's a metal chair. Sure, it will start to think that all the chairs without the back are metal chairs, but if that's the case in their home, so what, it's right. If it understands anything wrong enough that it fails at its task it can always be corrected and its knowledge about the world as it sees it will increase. Now when performing tasks it can treat the chair as an abstract object, now that it can recognize it. It can memorize where it stands, it can learn to avoid it or push it or whatever, as long as humans correct its assumptions and choices. Now these abstractions could be abstracted even further. The idea is to let it do very simple things and then combine them into larger tasks, much like programmers think about and solve programming problems: If you want to solve a large problem and you don't know how to, you break it into smaller pieces until you get a piece, that is simple enough to be solved. You solve it and see the next piece. Then you combine the solutions to a solution to the bigger problem and you finally end up with the first and biggest problem getting solved. This robot 'learns' the exact opposite way.
It seems to me that the biggest concern in this case is abstracting the objects it 'sees' into such a form, that they take minimal memory but can still be used in the recognition process.
That came out as ranting. I have no knowledge in the subject and have no idea what I'm talking about but that should make this a good enough Slashdot comment.
Re: (Score:2)
I have no knowledge in the subject and have no idea what I'm talking about but that should make this a good enough Slashdot comment.
You're going to fit in well here!
Re: (Score:2)
Congrats on understanding what it takes to make a successful slashdot post.
Commiserations on entirely failing to grok what this robot is all about.
The key principle this robot uses to sense/model it's surroundings is what it's builders are calling "reification", which they've just published a book about. This is a way to bridge the divide between fuzzy (and semantically empty) sensory data and a symbolic (and semantically rich, if you choose to make it so) model of it's environment. The idea is simple (and
Re: (Score:2)
Who wants it to take over the world? I can picture it coming in a box, some assembly required, then its first baby steps would be to learn the environment i.e. the household it'll work in: the couch. the fridge, the carbon based unit that will give it a 5 year mission or until the warranty expires, the domestic US beer it will leave in the fridge, and so on.
The couple have got their priorities straight. With a smug rubbing of the hands, 'Now that the refreshments can be brought to us, what shall we work on
Basil?! (Score:2, Funny)
I can see it now... (Score:3, Funny)
Go east, to a place called Klamath. K-l-a-m-a-t-h. Find Vic. V-i-c. Ask for beer. B-e-e-r. *sigh* You are the chosen one. Find the beer. Be our salvation.
wants_beer = 1 (Score:3, Funny)
That's a simple algorithm:
if (object == person)
wants_beer = 1;
Sure there is going to be some margin of error in that algorithm, but it's going to be right most of the time.
Re: (Score:2)
people_want_beer=1
Because we don't want some smart ass java parsing tin can second guessing us do we?
we love male-bashing (Score:2)
When they brought him out for their recent wedding anniversary party, for example, they turned off his higher-level brain and had him dance around by dumbly bouncing from one lady to the next -- the way most guys function on the dance floor.
Was the quip after the EM dash really necessary? Now, I know that most women have experience with outlaw bikers, but there are a lot of decent guys out there. The problem is they're not outlaw bikers.
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slave.
So this is not beer as in "free"...?
Re: (Score:2)
http://beeradvocate.com/beer/profile/130/5088 [beeradvocate.com]
Re: (Score:2)