The cutest robot in the classroom!WALL-EV3 is shaped after Disney Pixar’s WALL·E (Waste Allocation Load Lifter – Earth-Class), a fictional trash compactor robot left back on Earth to clean the planet from garbage, in a not-so-distant super-consumistic future.WALL-EV3 is built out of a single LEGO MINDSTORMS Education EV3 set 45544.WALL-EV3 has two triangular shaped treads driven by two EV3 Large Motors, and rotating head and arms driven by the EV3 Medium Motor. The EV3 gyro sensor allows the robot to drive perfectly straight, and turn precisely, even if the treads slip when travelling on uneven ground. It’s easy to attach an EV3 Color Sensor looking down on the ground, to enable WALL-EV3 to follow a line. Thanks to the EV3 Ultrasonic Sensor, WALL-EV3 can navigate while avoiding obstacles, or can follow your hand.DemoWALL-EV3 drives preciselyWall-EV3, thanks to the Gyro Sensor, can drive perfectly straight and turn accurately, unlike normal wheeled robots. In fact, even if the two wheels of a differential drive mobile robot travel at the same (nominal) speed, the robot might drift left or right.
This problem is due to light differences in motors, slipping of the wheels, uneveness of the ground, bumps, friction or external disturbances. For such a mobile robot, turning by an exact amount of degrees is even more difficult.But not for WALL-EV3! The Gyro Sensor reading is used as a feedback for a proportional controller that outputs the steering command for the Move Block. So, if the robot drifts, the Gyro heading changes and the controller adjusts the steering in order to make the robot travel straight again.Check out its outstanding performance in the video!Guessing Game for LEGO WALL-EWall-EV3 can play a simple number guessing arcade game. The rules are simple. In each turn, WALL-EV3 chooses a random number from 2 to 8, then it wait for you to guess if the next number will be higher or lower. You express the choice by pressing the right or the left button that are on his hands. Once you make you guess, WALL-EV3 shows the number he was thinking. If you are right, he cheers, and you get a point, otherwise he’s disappointed and the life bar decreases.
You can make 4 mistakes before the game is over. At that point, your final score is shown. Check out the video of LEGO WALL-E guessing game!WALL-EV3 is ready to go! EV3 project file that comes with the commercial license includes a set of programs.The quality of the building instructions is comparable to the LEGO official ones . The building steps are detailed and clear.WALL-EV3 can be built with the parts from LEGO MINDSTORMS Education EV3 core set 45544.Each PDF comes stamped with your name and license, to ensure product authenticityUsersBuilding InstructionsProgram FilesLicense TypeCommercial UseLEGO fans & teachersPrintable PDF documentNot includedFor personal use and public schools onlyNOThe transaction is manually reviewed for eligibility, so please allow up to 24 hours to receive the material at the email address connected to your Paypal account. pany OwnersPrintable high-quality PDF documentIncludedFor commercial activities and private schoolsYES Secure Paypal transaction.In the act of buying, you accept the following terms:You cannot share, resell or redistribute the material in any way with third parties.
You cannot use the material for other uses than the one allowed by your license.The material comes encrypted and protected, and cannot be extracted or transformed.Any infringment to the above terms is considered a punishable criminal offence.Back in February, Lego announced that it would be putting Angus MacLane’s WALL•E Lego Ideas model into production. And today, courtesy of the SmythsToys website, we might finally have our first look at the official Lego version of WALL•E. There’s a chance these images might be fake, created to serve as placeholders on the SmythsToys website until the real set is eventually released. But that CG Lego model of WALL•E doesn’t appear anywhere else online according to Google image search. And it’s doubtful that a toy store adding countless items to its catalog every day is going to go to that much trouble to create a placeholder image. So we have every reason to believe these are legit.Angus’ take on WALL•E that he submitted to Lego Ideas was already adorable, but somehow Lego’s official builders have managed to make the robot even cuter.
It’s all in those eyes. The SmythsToys website also claims the set will be available starting on December 1, with a price tag of €57.99, or about $65 in US dollars. But the folks at Brickset think it will probably be priced like similarly-sized sets at around $40 here. Not that price matters, because WALL•E fans will easily pay a small fortune for this set. It’s the waiting until December that’s the real problem. Wall-E recreated as a working robot using Lego Mindstorms 03.04.2012 :: 12:04PM EST Canadian Lego robotic expert Marc-André Bazergui has created the masterpiece depicted in the video above. He’s taken a Lego Mindstorms kit and managed to recreate Wall-E from the well-received Disney Pixar movie. If you aren’t familiar with the Lego Mindstorms series line of products, it’s a piece of kit that allows you to create working robots out of the famous building blocks. To get a creation to do different things, like interact with its environment or be able to move around according to the light levels in a room, Lego created the NXT block.
A computerized “brain” of sorts, the NXT has the ability to control three different motors and four different external sensors. That control can be tweaked through a USB connection to a PC where commands can be issued. In the case of the Lego Wall-E, Bazergui made use of three RCX motors connected to his NXT brick that allow his creation to transform. Just like his movie counterpart, Bazergui’s version of the lovable character can wave, move his eye cylinders, and sense when there is an object or person near him. It’s not a perfect replica, but it’s a herculean effort that we certainly couldn’t recreate. In that regard, it took Bazergui over 250 hours to put this model robot together, with countless more in the small changes he has made over the two-years Wall-E has been in operation and travelling the world to be displayed at different shows. Read more at The NXT Step, via Inhabitots.“A central question in protein evolution is the extent to which naturally occurring proteins sample the space of folded structures accessible to the polypeptide chain.”
Thus begins a new paper on sequence space for proteins, a concept that has been key to work by leading ID theorists Douglas Axe, Stephen Meyer, and William Dembski. This is the question: Out of the vast space of possible amino acid sequences, how many can fold into functional proteins? ID argues that functional space is such a small subset of sequence space, the probability that a blind search will find any is vanishingly small. Nine researchers led by some of our Seattle neighbors over at the University of Washington, publishing in Nature, decided to investigate how much of the sequence space nature has sampled. It’s obviously far too big a space to search, so they limited it to just “repeat proteins” — those that use certain structural motifs over and over. To our knowledge, all designed repeat protein structures to date have been based on naturally occurring families. These families may cover all stable repeat protein structures that can be built from the 20 amino acids or, alternatively, natural evolution may only have sampled a subset of what is possible.
By applying experimental protein design, they show that you can get many more potential proteins by simply repeating certain “building blocks” over and over, something like assembling Lego pieces blindly. They manufactured some Lego-like protein kits by generating scads of “a simple helix-loop-helix-loop building block” and putting them together using an automated process. Out of 83 they built, 44 showed a stable fold. But is this experiment about evolution or intelligent design? We have shown that a wide range of novel repeat proteins can be generated by tandem repeating a simple helix-loop-helix-loop building block. As illustrated by the comparison of 15 design models to the corresponding crystal structures (Fig. 4), our approach allows precise control over structural details throughout a broad range of geometries and curvatures. The design models and sequences are very different from each other and from naturally occurring repeat proteins, without any significant sequence or structural homology to known proteins (Extended Data Fig. 8).
This work achieves key milestones in computational protein design: the design protocol is completely automatic, the folds are unlike those in nature, more than half of the experimentally tested designs have the correct overall structure as assessed by SAXS, and the crystal structures demonstrate precise control over backbone conformation for proteins over 200 amino acids. The observed level of control over the repeating helix-loop-helix-loop architecture shows that computational protein design has matured to the point of providing alternatives to naturally occurring scaffolds, including graded and tunable variation difficult to achieve starting from existing proteins. We anticipate that the 44 successful designs described in this work (Extended Data Fig. 9), and sets generated using similar protocols for other repeat units, will be widely useful starting points for the design of new protein functions and assemblies. Note that word “function” at the end. A search of the paper shows nothing about whether any one of the design models actually does anything.
Yet they seem to have one ear open to the possible whisper of Darwin speaking in the background: Naturally occurring repeat protein families, such as ankyrins, leucine-rich repeats, TAL effectors and many others, have central roles in biological systems and in current molecular engineering efforts. Our results suggest that these families are only the tip of the iceberg of what is possible for polypeptide chains: there are clearly large regions of repeat protein space that are not sampled by currently known repeat protein structures. Repeat protein structures similar to our designs may not have been characterized yet, or perhaps may simply not exist in nature. The authors only mention evolution twice. It’s not really a focus in this paper. The word “design,” however, appears a whopping 74 times, even before the Methods section. They did interesting and important work. But lest anyone think their conclusion weakens the arguments of Axe, Meyer, and Dembski by expanding the potential functional space accessible to random search within sequence space, let’s apply a heavy dose of realism.
They sampled only part of the “repeat protein” portion of sequence space. They began with “building block” motifs that already fold (helices and loops). They used only left-handed (homochiral) amino acids. They did not test to see if any of the stable structures perform a function. They did not test to see if any of their structures could interact with other proteins or structures (for this problem, see this earlier article on this subject). Their work was highly dependent on intelligent design (i.e., their own). You could liken their results to a robot programmed to assemble Legos according to a rule: “fasten, twist, repeat.” If the Lego pieces are already designed, the algorithm can say nothing about where the pieces came from. As all kids know, the holes in Lego pieces have to be spaced properly to fit together. Similarly, amino acids need to be properly sequenced to fold into a helix or loop. If that’s a given, it’s not surprising that you could generate quite a few unique structures by the algorithm “fasten, twist, repeat.”
Even WALL-E the robot could do that without thinking. Whether anything worthwhile would result is dubious. Actually, you can assemble a WALL-E robot using Lego pieces now. The Lego company offers that and many other elaborate, complex kits that go well beyond the simple building-block sets from decades ago. A kid could put the WALL-E pieces together and show off his pride and joy in a matter of hours or maybe even minutes. But could nature pull that off by blind search? Think of the programming that would be required to get WALL-E to assemble his likeness out of Lego pieces! It’s intelligent design all the way down. Here’s the take-home: Despite a hint of “protein evolution” in this paper, the experimental evidence has again vindicated ID. Without a mind directing assembly of amino acids according to a design goal, nothing interesting will happen by chance or repetition by an aimless process. Sequence space is too vast and functional space too vanishingly small to expect success by blind search.