Why LEGO succeeded

1. LEGO makes toys. LEGO doesn’t produce weapons, it doesn’t produce soap or soup, it produces toys. LEGO has been around long enough for all of us to have played with it when we were kids. We know how they work, we like what they do, and maybe we wish that we were still playing with them right now (especially since they’ve gotten even cooler). The memories attached to LEGO (as with other toys) are unusually positive and emotional. Campbell or Clorox, to name two other companies which recently started to try to transform customers into innovators, fail to spark the same kind of joyful memory and enthusiasm as LEGO. Stefan Lindegaard wrote two great posts on the mistakes they seem to make on their OI platforms. I think that they could more specifically learn from LEGO. Here’s how:

2. (Nearly) all LEGO products are customizable, educational and technical. Customization goes very far at LEGO: on the LEGO factory website you can design your own houses, animals and spaces using something close to the software that LEGO designers use. If you wish, you can order the parts to your virtual construction and LEGO will send them to you. Parents who buy LEGO prefer toys that help their kids learn and develop, as opposed to toys that are just ready-to-use once they’ve torn them out of their packaging. Building with LEGOs makes kids active and apparently more technically inclined–they can either follow the directions to build things like police stations and pirate hideouts or use the pieces to invent their own model. LEGO seems to encourage kids to leave the beaten path. So kids who like LEGOs (and especially LEGO technic) are more likely become tech-savvy adults (and parents) that are easy to tap for the Open Innovation effort.

3. The gap between user and developer is relatively small with LEGO. As opposed to soap (or soup), you buy LEGOs because you value the challenge of building and the idea of making your own product. Most products are used in a much more limited sense. To use soap (or Windows, actually) you don’t need any of the skills that you would need to develop it. For a few years, to use computer software (this was true until MS-DOS) you needed some rudimentary knowledge of programming. Before Windows, computers were products where the line between developer and user was thin, which made it easier to appeal to users for help in development: Open Source communities emerged. And making a product more “user-friendly”, generally means to make it less (obviously) technical, hiding the technics far below the user interface.

4. LEGO’s OI challenges are embedded within a community. With videos, blogs, pictures from users, downloadable pictures, and online support, the Mindstorms Nxt platform gives you the feeling that, 1) participating in a LEGO challenge makes you part of a worldwide community of shared interests and pleasures, and 2) that the company really cares about you and your ideas. An online form like the one on the spartan Campbell site just doesn’t give you this feeling.

5. LEGO’s challenges are precise while remaining open, e.g. “we challenge you to build a robot based on an arcade game”. We’ve written about the problem of formalizing a problem before. But to keep it short: the key element is specificity. Even if you are open for various kinds of proposals, it won’t do just to say “Send us anything you think could be useful.”

6. LEGO’s successful adaptation of offline toys and their design on an online platform gives you the feeling of entering a universe when you enter the website. This is something many companies aim at, although few of them suceed.

The lessons other companies can learn

Now, the question is: what can companies do if they don’t have a product as well-suited to OI as LEGO’s?

1. Be conscious that marketing a product for co-development is not the same as marketing the product. Emphasize the play. Try hard to show the playful aspect of your products: create animation videos, drawings, shoot videos with engineers passionate about the project, etc.

2. Identify the biggest draw.  Spot your company’s product that is most customizable, playful, technical and start your initiative with that. This is the product with the right audience for a participative effort. LEGO started with LEGO technic, but extended the program to include all kinds of LEGO bricks with the LEGO factory that demands less technical skills.

3. There are products more up or down the line from users to developers. If you have technical products that require greater competence for use, use them for you OI efforts.

4. Create a community. Show that you care about outside innovators. LEGO lets you ask questions, makes users interact, mentions those who have contributed to an idea. Campbell, on the other side, states in their contract that they will never explain the refusal of an idea and that they will only pay if your idea becomes a patent (ouch!).

4. Break it down. Be precise and appealing in your problem statement. Otherwise, you’ll lose your time reviewing answers that are not on-target, if you get any. Choose to create discrete, precise challenges rather than going for a catch-all. A catch-all statement will look like you don’t know what you want, and that means that others won’t know, either. Think about #2 and 3 to choose the right product for your Open Innovation début.

5. Create a universe. A picture of the CEO and a “Submit your ideas” button is not going to do the job. Campbell, for example, could rely on Andy Warhol’s taste for their soup and give its site more of a “pop” look to  give you the feeling that their soups are iconic and that contributing to the development of such a product is rewarding. Clorox could put up some animations of the products they already have, show drawings, present the first formula that led to their first product, etc.

All this obviously takes a lot of work and time, probably even someone in the company who is only in charge of Open Innovation. Companies that are impatient and want to find out what they can learn from the outside right away, and who’d rather like to start experimenting with opening their corporate context with more limited costs and effort, should try to use a website with a community that is already in place, with people that signed up because they are interested in sharing their ideas and solving problems wherever they may come from, a place designed from top to bottom for problem solving and innovation, by people who only think about how to make the experience of problem solving more rewarding. A platform like this.

Klaus-Peter Speidel

It’s Wednesday and it’s day two of the ALT Conference 2009 here in Manchester.

An early start for me as I am running my Hood 2.1 workshop on Web 2.0. We had fun last year, I am hoping to have a similarily good session this morning.

Due to a scheduling clash, it does mean I will miss David Sugden and Lilian Soon’s excellent Active learning with Mobile and Web 2.0 technologies workshop.

After the Wednesday keynote, over lunch is the poster session, and I shall be showing off my Glossy poster.

After the poster session I am hoping to attend the demonstrations looking at Xerte and Mindstorms Communication in Second Life.

After the ALT AGM I will be going to Learning Innovation which has two short papers, 240 Students’ experiences of wikis for a collaborative project: technology choice, evidence and change and 167 Enhancing University Curricula via Adventure Learning.

Final session of the day will be the Epigeum Award for Most Effective Use of Video Presentations. I was one of the judges so will be at this session.

In the evening is the ALT Gala Conference Dinner. Last year’s conference dinner was really good and some of you may remember this video I made of last year’s dinner.

Should be good, long and busy day.

I was talking with a friend recently about the need for physical device security.

This then strangely lead onto cracking safes, which resulted in pondering whether or not it would be possible to design, build and program a Lego Mindstorms device to crack a combination safe.

I then did a bit of research and found that his has already been done in python using an arduino and a few other electronic bits.

Assembly wise, the device would be fairly simple to construct. The main issue would be turning a wheel accurately enough to be able turn the combination lock a single number either to the left or right.

My proposed method of attack would be simply brute forcing the combination, to test this I would obviously need to have something like a four digit code using a fairly limited range of digits so that the number of possible combinations is not insanely high.

Summary

There are many ways (and sensors) available that can allow a robot to follow a line. I have experimented a few that are of interest.

• Single Light Sensor
• Two Light Sensors
• Mindsensors LineLeader Sensor (Intelligent array of 8 light sensors in one I2C package)

In this article I review a couple of standard ways of staying on track, and then review the new Mindsensors – Line Leader sensor.  I was part of a beta-testing group for this great sensor.

Single Light Sensor

Using on NXT light sensor, there

are a couple of possibilities for following a line that can be effective. The programmer can either code to follow the line itself, or the edge of the line.

Following inside the line offers the advantage of knowing the robot is on the line, but what direct do we turn of we fall off? If the robot falls off of the line, which direction should it turn to return to it? As the robot drifts back and forth on the line, the programmer must try to correct its course to stay on the line. This method is mostly impractical.

Edge following offers the advantage of knowing the direction to turn in order to stay on the line. It is generally a faster, more accurate method for following a line. You select the right or left side of the line to follow, and code the robot to turn left if the light sensor reports BLACK and right if WHITE. This method allows a robot to follow the edge of the line through straight sections and curves. Is there a better method to follow a line?

Two Light Sensors

Using two NXT light sensors, there are also a couple of useful configurations to review. Sensors are generally set side by side on the front of the robot with either both inside, or both outside the line. With two sensors (left and right), more accurate line following can be achieved because as a line is lost on one side or the other, recovery is possible because we know which side lost the line.

Placement of the light sensors is very important so that only one sensor at a time could be on the line. As can be seen in the illustration, as the robot drifts from one side to the other, one sensor contacts the line and the robot can react accordingly.

Coding is similar to using one light sensor following the edge of a line, but you can let the robot run straight if both report WHITE or both report BLACK (depending on the configuration). This allows the robot to gain speed instead of oscillating back and forth (as much) as it must with one light sensor.

Mindsensors Line Leader Sensor

A more advanced method for following a line is to utilize three or more light sensors to follow a line. Many people have custom built line following sensor arrays, but Mindsensors has just released the Line Leader sensor for the rest of us. Not only does it contain eight (8) sensors in its array, the intelligent sensor also implements some very nice internal coding and a robust I2C interface to communicate with the robot.

Because there are 8 light detectors under the sensor, it is very easy to determine how to follow a line. The goal is to keep the line centered under the sensor. As the line moves left or right under the robot, it can compensate to center the line under the sensor. How is this done? Mindsensors has a good explanation in the Line Leader user guide.

Mindsensors took all of the hard work and math out of determining how to follow the line. There is a register for retrieving the STEERING value from the sensor. I have used the STEERING value successfully by supplying speed values to two motors. The following example code shows how to read the STEERING value from the sensor, and apply it to two drive motors.

int clip(int x, int min, int max) {
  if (x<min)
    return min;
  else if (x>max)
    return max;
  else
    return x;
}

While(true) {
//TWO MOTORS – DIFFERENTIAL DRIVE STEERING FROM LINE LEADER 
//GET STEERING FEEDBACK FROM THE SENSOR TO KEEP ROBOT ON THE LINE

  steering = (int) LL_Read(SensorPort, LineLeaderAddr, LL_READ_STEERING);
  motor[RIGHTMOTOR] = clip(70 + steering, -100, 100); //RIGHT MOTOR
  motor[LEFTMOTOR] = clip(70 - steering, -100, 100); //LEFT MOTOR
}

The clip function is a simple utility function that should be in everyone’s toolbox. It takes value returns it if it is between min and max. If outside the range, it returns min or max.

Mindsensors supplies a simple driver file that makes reading the STEERING value easier. We call LL_Read() with the LL_READ_STEERING constant to return the STEERING value suggested by the sensor based on where the line is. The last step is to determine speed value for the left and right motors. We ideally (in this case) want to travel straight at speed = 70. We add the steering value to the right motor, and subtract it from the left motor (within the range motors accept – [-100 to 100]). That’s it.

As the line drifts to the right (or robot to the left), steering becomes a negative number. The further it moves to the right, the bigger the number becomes to allow for correction of the robot.

If the STEERING value returned is -20, we set the motors to use the value to correct the robot’s steering.

RIGHTMOTOR power = 70 + (-20) = 50

LEFTMOTOR power = 70 – (-20) = 90

This causes the right motor to spin faster than the left turning the robot left to re-center the sensor over the line.

Your program would continue to loop, finding the next steering value and correcting the motors accordingly. The robot uses this feedback control to follow a line.

What if the robot takes advantage of the NXTs motor implementation and links the RIGHTMOTOR and LEFTMOTOR together? NXT firmware allows the motors to take advantage of the internal encoding for each motor to keep them running at the same speed (It can move in a straight line!). I often implement my drive motors with this configuration so the robot can easily move straight. Here is a quick code sample of implementing sync’d motors.

void _DriveRobot(int power, int steering) {
  if (steering >= 0) { //RIGHT TURN or STRAIGHT
    if (lastPower!=power || lastSteering != steering){
      nSyncedMotors = synchBA;
      nSyncedTurnRatio = (100 - (2*abs(steering)));
      motor[LEFTMOTOR]=power;
      lastPower=power;
      lastSteering=steering;
    }
  }
  else { //LEFT TURN
    if (lastPower!=power || lastSteering != steering){
      nSyncedMotors = synchAB;
      nSyncedTurnRatio = (100 - (2*abs(steering)));
      motor[RIGHTMOTOR]=power;
      lastPower=power;
      lastSteering=steering;
    }
  }
}

In this case, I have directly passed the STEERING value returned from the Line Leader to this routine with excellent success. Robot speed is determined by the POWER parameter (-100 to 100) to implement reverse, stop, or forward. The STEERING parameter (-100 to 100) determines left, straight, or right turns.

Um hacker sueco usou seu  Lego Mindstorms para escanear, resolver e escrever a solução de Sudoku.

O Lego Mindstorms é um briquedo utilizado para a educação infantil. Programar o “robozinho” é teoricamente fácil. Mas comcerteza fazer o robo escrever cada numero deve ter dado um trabalho danado.

[GIZMODO]

Swedish hacker [Hans Andersson] is no stranger to puzzle-solving robots. His prior work, A Rubik’s cube-solving robot called Tilted Twister, made waves through the internet last year. [Hans’] latest project only has to work in two dimensions, but is no less clever. This new robot, built around the LEGO Mindstorms NXT system, “reads” a printed sudoku page, solves the puzzle, then fills out the solution right on the same page, confidently and in ink. It’s a well-rounded project that brings together an unexpected image scanner, image processing algorithms, and precise motor control, all using standard NXT elements.

The building instructions have not yet been posted, but if the video above and the directions for his prior ’bot are any indication, then we’re in for a treat; he simply has a knack for explaining things concisely and with visual clarity. The source code and the detailed PDF diagrams for Tilted Twister are as gorgeous as his new robot’s penmanship.

[thanks Eric]

This weekend I bought the LEGO Mindstorms NXT 2.0 which has, I believe, has replaced the older type – the 1.0.

What is different? I think there are several items like the Blue tooth module and the software has various bits that allow you to tweek and customise the operations of the blocks within the programming. If I sound like a novice to this then you’d be correct!

To help me, as always, I purchase books. What?! I hear you cry. I know it’s very last century but there is nothing quite like a good reference book and especially true if they’re written well, illustrated and don’t make any pre-judgements regarding the readership.

I have several examples in my library (both as e-books and paper backs) ranging from ‘The Missing Manual’ series, some ‘… for Dummies’ (be very, very selective here! And, these: The LEGO NXT Mindstorms One-Kit Wonders and Unofficial Inventors guide.

The great thing about these is that there is a companion website to accompany them here. Here you will find the forums for the LEGO community and resources like these.

More to follow!

This morning on TVNZ, the breakfast show featured Lego Robotics. For a mere $500, you get the combined versatility of lego building systems with an intelligent microcomputer featuring a 32 bit microprocessor, a large matrix display, 4 input and 3 output ports, and Bluetooth and USB communication link. Three interactive servo motors, an ultrasonic sensor, two touch sensors and a colour sensor are included, in case you feel your child is not nerdy enough.

Lego has evidently come a long way from the time when anything other than an eight pin building block in one of the primary colours was considered innovative.

Her Goatiness: I don’t understand why children need all this stuff these days. When MY kids were little, they were quite happy with a stick and a box covered in mud. You didn’t have to spend $500 on presents. You could wrap up a rock; kept them occupied all day. I remember when Andy got a little tool set *sigh!* He sawed the leg off his high chair.

Let that be a lesson to us all. Husband did not spring into this world fully formed as an agent of destruction. No, the seeds were sown long ago.

Now it is I who reap the rewards.

Mwah hah hah! HAH HAHAHAAAARGH!

Taller de Robotica Nivel Basico 1 -  Robots tipo Animal

GRUPO 1

4 Sabados, del 5 al 26 de Septiembre del 2009.

Horario: 9 – 12 AM

Inscripciones Abiertas

Cupo limitado.

The collector is a more complex robot building on concepts learns from AreaBot.  The robot covers are much area of a closed arena as possible collecting Mindstorms NXT foam pucks, and delivering them to a central home base (light source).  The following represents the sensors, drivers, and behavior hierarchy to accomplish the task.

See all of the collector robot articles here.
Download the Code: Download: bbPuckBot.zip
See the video here.

Behaviors in Detail

I have reviewed the sensors and drivers in previous posts, so here I will focus on new behaviors, and discuss the big picture.  I have described CRUISE, BUMP ESCAPE, and BUMP FOLLOW in posts for the AreaBot.

LIGHT ESCAPE – If a light source is too bright, get away

Light escape is the highest priority and key to collecting pucks in a central home base location.  Although it has nothing to do with collecting anything, this behavior is the mechanism for dropping off the pucks at home base.  When the robot approaches the light source (with or without a puck in its grasp), and gets close, this behavior is triggered.  The robot backs up (leaving the puck it was pushing behind) and spins away to find more pucks.

Light escape is a relatively small behavior that relies on the differential light sensor as a trigger and the generic escape sequence to escape.

HOME LIGHT – if a light source is in view, move toward it

Home Light is a behavior that is triggered when the robot see enough light to determine it sees the home beacon, and attempts to move the robot toward it.  The differential light sensor is employed to determine the difference between left and right light intensity, and uses that value to steer the robot toward the light.

In an ideal situation, the robot will home in on the light while also pushing a puck.  In this way, pucks are delivered to the light source.

DARK PUCK – If a puck is captured and home is not in sight, turn toward it

Dark Puck is a departure from the collector robot from my reference book.  The original behavior was called DARK PUSH.  When the robot encountered a puck it could push it.  In the book, pucks were detected by turning toward them, and only pushing them if there was a light.  If no light beacon was seen, the robot would execute an escape sequence.

It was not practical to detect pucks with my robot using the IR proximity sensors, so I needed another way to increase the odds of moving pucks to the home base.  Dark Push applies similar principals to Dark Push by triggering when the robot is pushing a puck, and facing away from the home base beacon.  Dark Puck detects a captured puck using a legacy light sensor pointed down into the puck catch.  When detected, and the differential light sensors report no beacon, the robot attempts to turn (without loosing the puck) toward the light source.  If successful, HOME LIGHT may take over and move the puck to home base.

WordPress Tags: Collector,Robot,Behavior,Diagram,AreaBot,Mindstorms,task,Behaviors,CRUISE,BUMP,ESCAPE,HOME,DARK,PUCK,PUSH,concepts

Some of you may have noticed that my Collector Robot has more than two light sensors hanging off the sides…  There is an archaic bumper (design from the original Mindstorms 1.0 kit) and a legacy light sensor buried in the bumper.  There is also a couple of white arched technic pieces under the bumper.

I thought I would go into more detail on this design because the implementation was interesting.  This robot is designed to find and move Lego NXT pucks around.  It does not specifically search for pucks, but happens upon them because it is able to cover all areas of the arena.

Download the driver here: BumpLightCombo.h

Technical Background

The bumpers give the robot protection from walls and objects and trigger several behaviors within the robot to perform tasks like escaping a collision and following a wall (just like Areabot).

There is a “puck catch” under the bumper that is designed to either direct pucks into the middle where a light sensor can detect the black color, or deflect pucks to far to the right or left away from the wheels.  If a puck is detected in the catch, various behaviors are triggered to increase the chance the robot will deliver them to home base.

Sensor Implementation

Sometimes there is an opportunity to combine sensors together into one port that requires no additional hardware.  It requires a little bit of ingenuity and programming creativity, but the results can give you more sensory power without using additional input ports.

For my Collector Robot, I wanted to implement a front bumper to detect collisions, and a light sensor to detect captured pucks. As knowledge and experience luck would have it, I was able to combine the bumper and down pointing light sensor into one port because the sensors are not needed at the same time.

There are a few compromises that need to be understood to configure the sensors using only one NXT input port.

• The left and right bumpers are connected together to provide ONE bumper on the front of the robot.
  • A compromise with this configuration is the loss of ability to detect left or right collisions.  I used to think this was bad, but I found out it is not that big of a deal.  In my case, bumping is used to escape from a collision or for following a wall.  In both cases, I control the turning directions anyway, so there is no reason to implement left and right bumpers.  Escape randomly turns away from the wall.  Wall following always follows walls on the right side, so a spin gets it into position easily.
• The legacy light sensor is also connected to the same port as the bumpers and is used to detect pucks in the “puck catch” area.
  • What happens, is the light sensor value is read as long as there is not a collision.  If there is a collision, the value goes to 100.  No problem for collector robot because I am continually monitoring for the presence of a puck when not hitting a wall.
    • You must implement bumpers that are normally open (not pressed) in order to use the light sensor.  These are not the best for bumpers because it takes more force to press the buttons than to release them.  Collector Robot gets beat up a little, but it is good for its sole   I can live with that.
    • When the bumper is pressed, the light sensor is useless.  This can be an issue if you need the bumpers and the light sensor at the same time.  In my case, a collision was more critical than whether or not I could detect a puck in the collector.

I wrote a driver that allows me to abstract all of this logic into a few functions I can call to check the sensor(s) status.  It is not complicated, but lets me concentrate on the rest of the code without remembering the implementation.

Code Listing

#define FRONT_BUMPER S2  //DEFAULT INPUT PORT FOR BUMPER SWITCH SENSOR
#define LIGHT_DOWN S2  //DEFAULT INPUT PORT FOR BUMPER SWITCH SENSOR 

const int kLightSensorDark = 24; //LIGHT SENSOR BLACK THRESHOLD 

//INITIALIZE FRONT BUMPER TYPE AND MODE
void BumpLightCombo_Initialize() {
  SensorType[LIGHT_DOWN] = sensorReflection;
  SensorMode[LIGHT_DOWN] = modePercentage;
} 

// CHECK THE SENSOR FOR BUMPED.  MUST BE NORMALLY OPEN AND CLOSED ON TRIGGER!
bool bumper_isBumped() {
  return (bool) (SensorValue[FRONT_BUMPER] >= 99);
} 

// CHECK THE SENSOR FOR BUMPED OR NOT BASED ON VALUE AND CONFIGURATION
bool lightDown_isDark() {
  return (bool) (SensorValue[LIGHT_DOWN] <= kLightSensorDark);
} 

// CHECK THE SENSOR FOR BUMPED OR NOT BASED ON VALUE AND CONFIGURATION
bool lightDown_isLight() {
byte _value = SensorValue[LIGHT_DOWN];
  return (bool) (_value > kLightSensorDark + 5 && _value <99);
}

cccc

Sorry this video took so long to post.  Some time in the past two weeks, my microphone/Windows 7 combination started acting up.  The voice was recorded choppy and awful.  I sounds like two drivers are competing for control of the microphone processing, but I can’t tell for sure.  I guess those are the breaks with release candidate software…

Any way, here is the missing video.

It shows the robot trying to move about in my arena.  The first part shows AreaRover bouncing off the walls and failing to enter the second chamber because the door is not very large.  Eventually, the robot would make it into the room, but we like efficiency.

By adding wall following to the behaviors, the robot is able to follow a wall around the corner and into the 2nd chamber very easily.  I experimented with using the Ultrasonic sensor to follow a wall on one side, and bumper collisions to follow the wall on the other side to add variety.  It just goes to show you that behaviors can be layered in a robust manner fairly easily.

WordPress Tags: AreaRover,Video,robot,chamber,Ultrasonic,sensor,collisions,behaviors

I just came back from Safeway. Before that, I was eating dinner. Before that, I was at the 2009 FIRST Lego League Qualifying Tournament.

At the tournament, you have to program a NXT Mindstorms robot to do certain missions that you pick. You also get scored on your teamwork, robot design, and project that has to be based on the theme. (By the way, this year’s theme was about safe ways to get to places. Basically, transportation.) On the practical part (the missions), we got 9th place out of 12. The good part? We were the first team in our region to finish a round on the red bridge. That was kinda cool.

We didn’t get any awards or anything, but all in all, it was fun. The red bridge thing was even more cool.

Learn more about the FIRST Lego League, the NXT Mindstorms kit, and everything else at:
http://www.usfirst.org/roboticsprograms/fll/ <—–FLL Site
http://mindstorms.lego.com/ <—–NXT Mindstorms Site

Ryan

Sebenarnya artikel ini cocok untuk adik-adik yang berusia mulai dari 7 -12 tahun, tetapi kalau teman-teman ada yang mau belajar ya tidak masalah…kan ngejar ilmu sampai ke negeri tirai bambu…begitu kata petuah orang tua kita.

Sebenarnya saya membeli Lego Mindstorms NXT awalnya hanya untuk mencoba mengalihkan perhatian anak saya si Omy yang berusia 3 tahun dari hobby membeli dan mengoleksi berbagai tipe mainan mobil-mobilan! Selain itu agar dia interested ke mainan robot dan sekaligus meningkatkan stimul daya logikanya…begitu kata para psikolog kalau berbicara di seminar. Dan yang jelas…ini tidak ada pesan dari sponsor!

Ketika saya akan membelikan Mindstorms NXT untuk si Omy, saya sempat menelpon dan bertanya beberapa distributor di Indonesia yang aku kenal. Versi Lego Mindstorms NXT ada dua tipe, yaitu :
1. NXT 8257
Versi ini memang untuk retail dan jumlah komponennya lebih sdikit dibanding versi yang satunya.


2. NXT 9797
Versi ini sangat support untuk education version. Jadi terserah ke Anda bila mau membeli.

Ketika saya bertanya harga, distributor di Bandung membandrol harga :Rp. 4,8 jt untuk versi NXT 9797, sedangkan distributor Surabaya dengan harga Rp 5,4jt untuk versi NXT 8257. Semuanya belum termasuk ongkos kirim. Wah kok lebih mahal harganya bila dibandingkan di internet, maka kuputuskan saja beli langsung di internet. Saya beli di US dengan harga Rp. 3 jt sudah termasuk ongkos kirim untuk versi NXT 8257.

Mindstorms NXT memang didesain untuk anak-anak sehingga tidak menyulitkan mereka. Sama saat kita belajar robot, Mindstorms NXT pun sudah dilengkapi dengan beberapa bagian, antara lain :
1. Otak (mikrokontroller),
2. Sensor (ada sensor suara, jarak, dll)
3. Penggerak (servo motor)
4. Software
5. Perangkat penunjang lainnya
Belajar menjalankan Mindstorms NXT sangat mudah karena semua sudah dibuat simple, sangat berbeda saat kita belajar membuat robot dengan mikrokontroler yang harus mengerti tentang bahasa pemprograman.

Oke…introductionnya mungkin cukup sekian dulu…ntar saya sambung ke munu inti belajarnya.

Salam,

Munadi A

I am excited about my new focus on helping universities, colleges, and private schools provide continuing, multi-dimensional value to their alumni through social media—and specifically, custom online communities.

The opportunities for engagement and exchange are rich and powerful in a higher education environment. Leveraging the strength of the profound personal connection through the “ambient intimacy” of online interaction can ultimately help increase giving, boost admissions referrals, and engage more alumni in meaningful ways. For alumni associations, the applications are very compelling:

• Increase investment in affinity products and institution-related activities.
• Enrich and deepen the institution’s “brand” experience for students, faculty, staff, alumni, and friends.
• Promote and strengthen the foundations of affiliation (class year, school/college, dorm/Greek organization, student activity, professional focus)
• Position the institution’s community to positively impact loyalty-related outcomes, such as annual giving, association membership, reunion attendance, and etc.

The challenge is maximizing the ongoing value of an online community by balancing institution content control with user participation. Remember, it’s about relationships—building on the ephemeral—memories, experiences, and bonds based less on practical deliverables and more the emotions of affiliation.

In his August 2009 Wall Street Journal article on corporate branded communities, The Fans Know Best, Dr.Uptal Dholakia of Rice University contends:

“Allowing discussion and activities like networking and socializing leads visitors to participate in the site for emotional and social reasons. It keeps them coming back, and thus strengthens the bond between them and the company (and each other). Part of giving up control is also giving visitors the freedom to complain and criticize the brand, or to wax lyrical about a competitor, to their heart’s content.”

Therefore, our task becomes more focused on orchestrating, monitoring, and responding–rather than drafting, editing, and deleting.

Though Dr. Dholakia is speaking of the corporate sector here, I think the ideas can be applied to association communities, as well. Visitors frequent communities, because they enjoy the experience—not because it is something on the to-do list. Think about the silly quizzes on Facebook. The “fun factor” should not be underestimated as a key driver of engagement. Yet, it’s possible for universities and colleges to deliver real value in the process. We must not forget the truly “social” component of social media—providing a platform for witty banter. And universities alumni already have a built-in affinity. The potential is boundless—to create what I call the “perpetual reunion.” It’s 365/24/7 engagement.

Dr.Uptal Dholakia offers a high-octane example of community-building savvy from the corporate world:

“When Lego Group set out to develop Mindstorms NXT, the latest version of its game for building programmable robots, it enlisted help from a group of adult enthusiasts whom it found on Lugnet.com, the largest unofficial community of Lego fans. While the marketing target for Mindstorms is mainly teenage boys, the people that Lego reached out to were men in their 40s and 50s who knew each other from communicating and working together on elaborate Lego projects on Lugnet.com.

The group’s members, according to a Lego spokesman, contributed ‘incredibly valuable insights’ in hardware, software, design and usability based on their own experiences. The company credits the group with helping to make Mindstorms NXT appeal both to adults and ‘a new, younger generation of robotics enthusiasts.’”

Just think of the application for a university community—building connection between alumni, faculty, and staff—students and even prospective students. Not all colleges and universities are systematically monitoring their “unofficial” user-driven groups on LinkedIn, Fan Pages on Facebook, and Twitter feeds. But tracking and engaging these communities can provide a wealth of opportunities, alliances, ideas, innovations, and energy.

What are your thoughts? To learn more about unleashing the power of a managed online community, contact me: ewright @ publishingconcepts.com.

PCI – the data company
creates and manages alumni web communities and publishes alumni directories for educational institutions. Our clients are more severely challenged to find ways to fund their missions than ever before. PCI’s products and services help them meet the challenge by driving alumni engagement and maximizing contributions through technology expertise, and best practices.

totalmente mio . 326 dlls, pero es mio!!!![envidiame]

por cierto 5 hrs armandolo pero mi bebe reconoce colores

Jouer au basket ball avec le Mindstorms: sur la brique Lego, on sélectionne Gauche ou Droite par intervalle de 15 degrés. La validation se fait avec le bouton, on sélectionne ensuite la puissance de tir avec la télécommande, on valide avec le bouton et panier.

Une petite vidéo pour illustrer le fonctionnement:

Quelques photos du Mindstorms basket ball:

La télécommande au premier plan est composée d’un moteur et du bouton tactile.

Le panier de basket les points sont comptabilisés avec le capteur de lumière. Une partie compte 5 tirs, à la fin le score apparait sur l’écran de la brique.

Há algum tempo atrás fui convidado a participar do Mestrado e então participei de algumas disciplinas, entre elas Inteligência Computacional (uma das disciplinas que mais me chamou atenção).

Nesta disciplina foi solicitado pelos professores, que os alunos apresentassem em uma primeira etapa “O que pode ser feito utilizando-se Inteligência Computacional?”. Então forá demonstrado sobre um artigo desenvolvido no NCE-UFRJ focando no tema de Reconhecimento automático de placas de veículos, muito interessante.

A partir deste trabalho foram solicitados mais dois outros com o intuito de dar prosseguimento ao tema demonstrado na primeira etapa. Estes duas etapas seguintes teriam que se basear em apresentar alguma idéia de como seria um protótipo e quais técnicas de inteligência computacional poderiam ser aplicadas, já na terceira etapa um protótipo simples e demonstrando como foi estruturado a inteligência nele.

Com isso, acabei mudando totalmente o caminho do trabalho que tinha realizado, pois comecei com reconhecimento de placas e modifiquei para robótica ressaltando que pensei da seguinte forma: “Já que terei que apresentar algum protótipo irei me basear no que já possuo conhecimento.” e assim foi feito busquei idéias sobre robótica e Java.

Depois de uma enorme busca, encontrei um produto que me motivou muito Lego Mindstorms Nxt e então montei uma apresentação simples abordando esse produto da Lego.

Segue abaixo a apresentação:

E veja alguns vídeos do próprio site:

Vídeos Lego Mindstorms Nxt

Bom, se passaram por todos os slides verificou que foi citado que os programas que estes modelos podem suportar podem ser escritos também em Java!

Entretando pode surgir a pergunta: “Mas e aí, você implementou alguma inteligência e aplicou em algum modelo da Lego real?”, a resposta é não basicamente porque faltou recursos financeiros para possuir um “brinquedo” desses.

Então a idéia foi: “Por que não simular a ação da inteligência que poderá futuramente ser implementada no robô?”

Ou seja, essa foi a proposta para o último trabalho e que será exposto no próximo post. (Afinal este blog tem que começar a render assunto!!)

Até,

All of this was built and programmed using the Lego Mindstorms NXT Retail-kit. Awesome!

From Tilted Twister:

Tilted Twister solves Rubik’s cube fully automatically.
Just place the scrambled cube on Tilted Twister’s turntable. An ultrasonic sensor detects its presence and starts to read the colors of the cube faces using a light sensor. The robot turns and tilts the cube in order to read all the faces. It then calculates a solution and executes the moves by turning, tilting and twisting the cube.

Here’s a video:

I’m hosting a team building workshop today and we are playing lego! We’ve all got Mindstorms kits to build and program robots and it is great fun!