Season is over. You took part in amazing competitions and worked hard for your success.
Now it’s time to lay back and relax.
Or is it?
Offseason provides a great opportunity to enhance your team’s robotics skills for when the next season begins.
CoderZ has just the thing for you.
An exclusive offseason offer, just for FLL teams!
We understand that during season, not every team member has the chance to program and work on those computational thinking skills. That is why, we at CoderZ, are excited to bring to you CoderZ™ with Coding Robots™ course bundle, for FREE!
CoderZ is an online learning environment where kids learn how to program virtual and real robots within the STEM pathways. Problem-solving, critical thinking, computational thinking, teamwork, self-paced learning, formative assessment, robotics, classroom engagement: CoderZ includes all of these concepts and more.
Discovering different new ways to engage the new generations with robotics and with STEM related fields becomes a bigger challenge everyday. That is why, tools like CoderZ are being developed to give teachers, educators, and robotics experts the possibility to take a deep breath.
CoderZ’s new version, now compatible with the LEGO Mindstorms EV3 (through Lejos), enables students to program their own virtual robot and acquire 21st-century skills. Delivered with the “Coding Robots” curriculum, co-developed by Intelitek and Gary Garber, CoderZ becomes an scalable and effective way for students with different levels to experience the robotics world in class.
Having several gamified missions, motivates kids to accomplish them in order to move to a harder level. Also, CoderZ has a class management tool for teachers to track each student progress and activity.
Starting with a friendly drag-and-drop blockly visual editor, kids progress to code their virtual robot using Java.
Recently, the CoderZ team added to their previous FTC, First Tech Challenge, version, the new version mentioned before, which is compatible with the EV3 brick. Right now, the CoderZ team is offering a 14-day free trial which you can sign up for here.
CoderZ even gives you the option of driving and programming your virtual robot on the moon, taking into consideration friction and gravity. And of course, increasing the kids’ engagement with the robotics world. Although, for now, kids’ won’t be able to try their robot on the moon after they download the program, but who knows what Elon Musk will create in the next few years.
Pay some atención! CoderZ’s STEM learning environment is available both in English and in Español… Si señor!
This article has been automatically translated from German to English
Some weeks ago, I received the Meccanoid XL 2.0 as a review copy. Unfortunately, it was only a few weeks later that I found time to commit myself more closely with this new humanoid robot from Meccano. Even though I got the Meccanoid free of charge, this is a neutral report. Here are my first impressions after the assembly and the first hours of the „programming“.
The Meccanoid XL 2.0 is the successor of Meccanoid G15KS and its smaller G15 version. Even the G15 has received a successor with the Meccanoid 2.0 (excluding XL). The number of parts has been reduced slightly compared to its predecessor, and the previously existing building instructions for a dinosaur are missing on the robot now. There’s a new „Meccasaur“ Dino robot now as a separate product. Also accounted for, is the ability to control the robot through a Smartphone by controlling the movements in front of the camera. This option was apparently completely removed from the app and is also no longer available for the G15 or G15KS. Newly added are over 3000 new gestures and language editions, as well as possibilities of speech recognition. The understood vocabulary of the robot was so significantly expanded compared to the previous version. The Meccanoid XL 2.0 has a size of 1,20 m, what makes him to be really impressive, and an absolute eye-catcher.
The Assembly was largely problem-free; however I must confess at this point that I am a newbie in Meccano. The instructions could have been given in better quality, so it was difficult to identify building steps and the corresponding correct holes for the screws in some places. You should take special consideration on the cable guide, because this is neglected in the building instructions’ manual. Here planning and thinking is required, whereby the degree of difficulty is rather aimed at advanced hobbyists. Even the assembly time of 5-6 hours proves to me that this is not a robot Kit for beginners. The specified minimum age of 10 years here, in my opinion, is somewhat young. Certainly, children need assistance by an adult when reassembling.
The parts are different from what Meccano usually offers, not made of metal but of plastic. Meccano has already received criticism online for the plastic parts, but they did not disturb me. The motors of the robot parts made of iron would be more overworked than with new plastic model.
Unfortunately many of the components are very specialized, creating one’s customized building is complicated. The hope here is that a few days ago on the Meccano Facebook page, there was posted a video, belonging to a new „Meccano mega builds“ series. This series presented alternate building possibilities in combination with other Meccano sets. Also present is a video for a new „Mecca spider“, a robot spider based on the Meccanoid and the 25 in 1 4 x 4 off-roader set. Unfortunately, I have promised instructions in the video not yet on the Meccano site, but I have already informed the support team. Please more of such alternative models are for the meccanoid set!
The Meccanoid can be adjusted to different types of „Programming“. Movement can be recorded by the movement of the limb and play back by the push of a button. This is not of course the correct programming, but it can very quickly store movements, which can then be retrieved. This „programming mode“ is suitable for everyone who shuns the correct programming. Another mode is the recording of motion sequences with the Meccanoid app (for Android and iOS). In the app is a virtual robot available whose movements can be transferred to the real Meccanoid. This method also provides no proper programming, it also only records movements. Correct programming, however, is possible with the „drag and drop – programming“ in the app. Here simple programs can be put together, which is similar to how a flow chart is built. It can be used on events (inputs) such as time, engine movement, button pressure, etc be it responsive and affiliated movements, speech, LED color change and other operations will be launched. Here we can also easily learn how to program operations and programming constructions (loops, conditions). Since the Meccanoid contains no additional sensors, the possibilities here unfortunately are somewhat limited. The app offers an interactive tutorial with an English language edition and German subtitles. Appealing to children here is the ‚Coach Meccanoid‘ virtual robot that gradually step by step guides them on using the app.
Is the Meccanoid good for use in the classroom? No. With a construction period of 5-6 hours, the building period will take too long for teaching. The learning processes through movement of the robot offers no learning effect. The use of the built-in voice control and dialog function (which did not want to work with me in German), is based on volume which is not suitable for a class room. Drag- and -drop programming is certainly suitable for the classroom, unfortunately there is the lack of tasks set or instructions for the teaching of Meccano. The introduction to simple programming sequences can be taught with some adequate preparation. Additional advanced features give hope that the Meccano can provide a download portal for „open source programming“. Here you will find sample projects and libraries to control the meccanoid by third-party hardware.
As far as my impression of the Meccano Meccanoid XL 2.0, should you have questions or suggestions, you would like to use the comment function. Pictures and videos of the set up will be available here soon.
MathWorks stellt Release 2017a der MATLAB- und Simulink-Produktfamilien vor
Aachen/München, 9. März 2017 – MathWorks stellt heute Release 2017a (R2017a) mit einer Reihe neuer Funktionen in MATLAB und Simulink vor. R2017a enthält ein neues Produkt, die Automated Driving System Toolbox, für den Entwurf, die Simulation und das Testen von fortgeschrittenen Fahrerassistenzsystemen (ADAS) und automatisierten Fahrsystemen. R2017a enthält zudem Neuerungen im Bereich Big Data Analytics und Machine Learning ebenso wie Aktualisierungen für 86 vorhandene Produkte.
Neue Funktionen für Automatisiertes Fahren
Das Release 2017a umfasst die neue Automated Driving System Toolbox für das Design und Testen von ADAS und autonomen Fahrsystemen. Sie stellt neue Funktionen zur Entwicklung von Sensor-Fusion- und Tracking-Algorithmen bereit, die den Anwendern helfen, durch das Zusammenführen von Sensordaten aus komplementären Quellen neue und präzisere Kenntnisse über einzelne Verkehrssituationen zu erlangen. Anhand von generierten Verkehrsszenarien und synthetischen Sensordaten lassen sich Algorithmen testen und validieren. Mit weiteren Funktionen können komplette Kamera-, Radar- und Lidar-basierte Sensoren entwickelt werden. Durch die automatische Generierung von Code für den Sensorfusions- und Verfolgungs-Workflow lässt sich wertvolle Entwicklungszeit einsparen.
Von Data Analytics zu Maschinellem Lernen
Ein weiterer Fokus des R2017a liegt auf neuen Funktionen für Data Analytics, Machine Learning und Deep Learning. Neue Tools erleichtern die Skalierung und schnellere Ausführung von Algorithmen in MATLAB und Simulink. Dieser Vorteil kommt beispielsweise zum Tragen, wenn Anwender große Mengen an Bilddaten analysieren möchten, um Algorithmen zur Objekterkennung zu entwickeln.
Mit dem neuen Update ist es möglich, neuronale Netze vollständig selbst zu trainieren oder Transfer Learning mit vortrainierten Modellen zu verwenden, die bereits Tausende von Objekten erkennen. Anwender können das Training mit GPUs auf ihrem Multi-Core Computer oder durch Skalierung in der Cloud beschleunigen.
Das Update umfasst zudem Frameworks zur Objekterkennung, die helfen, Objekte mit Deep Learning noch präziser lokalisieren und klassifizieren zu können. Funktionen für Maschinelles Lernen sind bereits in die Classification Learner App integriert und helfen bei der Klassifizierung von Objekten. Ergänzt wird sie durch die neue Regression Learner App zum Trainieren von Regressionsmodellen mit überwachtem maschinellem Lernen.
Big Data leichter verarbeiten
Bei der Bearbeitung großer Datenmengen stehen Anwender oft vor technischen Problemen, etwa wenn sie Algorithmen entworfen haben und diese skalieren möchten, die Daten aber nicht in den Arbeitsspeicher passen. Zur leichteren Bearbeitung von Big Data wurden im Release 2016b Tall Arrays eingeführt, die bei großen Datenmengen dennoch eine vertraute Syntax bieten. Mit dem Release 2017a werden Tall Arrays auch in vielen Machine-Learning-Funktionen unterstützt.
Leichteres Arbeiten mit Simulink in der Cloud
Auch in Simulink erleichtern Neuerungen des umfassenden Updates die Arbeit mit großen Datenmengen. Zum Beispiel ist es nun möglich, Eingangssignale aus MAT-Dateien zu streamen anstatt sie in den Arbeitsspeicher laden zu müssen. Zudem können Nutzer nun mithilfe des parsim-Befehls mehrere Simulationen parallel ausführen – entweder auf dem eigenen PC oder in der Cloud.
Auf der embedded world 2017 in Nürnberg, 14.-16. März, können Sie sich auf dem MathWorks-Stand (Halle 4, Stand 110) persönlich mit einem Ansprechpartner austauschen
Updates der MATLAB-Produktfamilie:
Interaktive Aktualisierungen von Abbildungen im Live Editor (einschließlich des Titels, der Beschriftungen, der Legende und weiterer Anmerkungen) sowie die Möglichkeit, Live-Script-Ausgaben in andere Anwendungen zu kopieren
Heatmap-Diagrammfunktionen für die Datenvisualisierung
Mehr Funktionen für die Arbeit mit Tall Arrays, darunter ismember, sort, conv und Funktionen für sich bewegende Statistiken
Bayes‘sches lineares Regressionsmodell zum Analysieren der Beziehung zwischen einem Ausgang und einer Reihe von Prädiktorvariablen
Vektorautoregressives Modell zum Analysieren von Daten multivariater Zeitserien, einschließlich exogener Prädiktoren
MATLAB Production Server
Webbasiertes Servermanagement-Dashboard für die IT-Konfiguration und -Steuerung
Neural Network Toolbox
Deep-Learning-Algorithmen zum Trainieren von neuronalen Faltungsnetzwerken (CNNs) für Regressionsaufgaben mit mehreren GPUs auf PCs, auf Clustern und in der Cloud
Deep-Learning-Visualisierung für die von einem CNN-Modell erlernten Funktionen mithilfe von Bildoptimierung
Funktionen zur Übertragung von Gewichtungen von vortrainierten CNN-Modellen (AlexNet, VGG-16 und VGG-19) und Modellen von Caffe Model Zoo
Statistics and Machine Learning Toolbox
Regression-Learner-App zum Trainieren von Regressionsmodellen mit überwachtem maschinellem Lernen
Tall-Array-Algorithmen für Support Vector Machine (SVM) und naive Bayes-Klassifikation, Entscheidungsbäume mit Bagging sowie Lasso-Regression
Computer Vision System Toolbox
Deep Learning zur Erkennung von Objekten mit Fast R-CNN und Faster R-CNN
Automated Driving System Toolbox
Neues Produkt für den Entwurf, die Simulation und das Testen von fortgeschrittenen Fahrerassistenzsystemen (ADAS) und automatisierten Fahrsystemen
Updates der Simulink-Produktfamilie:
Simulink-Projektupgrade für die leichte Aktualisierung aller Dateien in einem Projekt auf das aktuelle Release
parsim-Befehl für die direkte Ausführung mehrerer paralleler Simulationen
Streaming für umfangreiche Eingangssignale von MAT-Dateien, ohne dass die Daten in den Arbeitsspeicher geladen werden
Reduzierte Busverdrahtung zur schnellen Gruppierung von Signalen in Busse und zur automatischen Erstellung von Buselement-Ports, um weniger Signalleitungen zwischen und innerhalb von Subsystemen zu benötigen
Automatische Port-Erstellung zum Hinzufügen eingehender und ausgehender Ports zu Blöcken beim Routing von Signalen
Laufzeitparameter für die Beschleunigung von Simulationsaufgaben und für das Verändern von Komponenten-Parameterwerten ohne erneute Generierung des C-Codes
Onshape-CAD-Import zur Verwendung cloudbasierter CAD-Baugruppen in der Mehrkörpersimulation
Zu den Signalverarbeitungs- und Kommunikations-Updates gehören:
Antenna Designer-App für die interaktive Auswahl und Analyse von Antennen mit den gewünschten Eigenschaften
Communications System Toolbox
Modellierung und Simulation für räumlich definierte MIMO-Kanäle in Mehrweg- und Streuungs-Übertragungsszenarien
LTE System Toolbox
MATLAB-Funktionen zum Simulieren von neuen 3GPP 5G-Mobilfunk-Technologien
Sidelink-Empfangsfunktionalität für die Simulation direkter Kommunikation über LTE-A ProSe auf Link-Ebene für Anwendungen in der öffentlichen Sicherheit und der Fahrzeugkommunikation
WLAN System Toolbox
Unterstützung der Generierung von Wellenformen gemäß IEEE 802.11ad
Zu den Codegenerierungs-Updates gehören:
Release-unabhängige Code-Integration zur Wiederverwendung von generiertem Modell-Referenzcode aus früheren Releases
Unterstützung von dynamisch zugewiesenem Arbeitsspeicher für die Simulation von MATLAB-Funktionsblöcken und die Codegenerierung
Generierung von HDL-Code aus Gleitkommaoperationen mit einfacher Genauigkeit nach IEEE-Standard
Unterstützung der Abtastung und Erfassung interner FPGA-Signale zur Analyse in MATLAB oder Simulink
Zu den Verifikations- und Validierungs-Updates gehören:
Polyspace Bug Finder
Codeüberprüfung für MISRA C:2012 Amendment 1 und neue Kryptografie-Routinen
Simulink Verification and Validation
Verbesserungen bei der Klon-Erkennung für die Refaktorierung wiederholter Bibliotheksmuster und Subsystem-Klone
Unterstützung von DOORS Next Generation für die Verknüpfung von Modellelementen mit Anforderungen und die entsprechende Nachverfolgung in DOORS Next Generation
Simulink Design Verifier
Virtualisierung der Auswirkungen des Timings von Zustandsaktivitäten auf die Slicer-Hervorhebung für Simulationen
Simulink Code Inspector
Unterstützung von Schleifen- und Zyklus-Operationen in MATLAB, Simulink und Stateflow
R2017a ist ab sofort weltweit erhältlich. Weitere Informationen siehe R2017a Highlights.
Folgen Sie @MATLAB auf Twitter, um mitzuverfolgen, was bei R2017a neu ist, oder klicken Sie auf der MATLAB Facebook-Seite auf „Gefällt mir”.
In 2014 UFACTORY built the first open source desktop robotic arm, ushering in a new era of affordable desktop robotic arms for consumers. uArm is an Arduino-powered desktop 4-axis parallel-mechanism robot, easy to use, has multiple accessories and open sourced. In Jan 2014, uArm went on Kickstarter and became famous overnight, leading to an exclusive interview with WIRED. A standout quote from the piece: “Thirty years ago Bill Gates promised to put a computer on every desk in America, an ambitious sentiment echoed by Wang and company … The most innovative aspect of the entire project is probably the concept of putting a robot arm on your desk”.
As the robot arm is moving to various industries, its users have expanded from relatively minority geeks to robot lovers. The demand for better and easier user experience is increasing.
January 23, 2017, UFACTORY returns again, announcing two robotic arms in uArm Swift Series. Swift is intended to highlight the elegant texture of the fuselage, lightweight and portable form and flexible movement, just like a swift. This series has uArm Swift and uArm Swift Pro.
uArm Swift enhanced the control algorithm and increased the accuracy by 50%, from 1cm to 5mm.
uArm Swift Pro adapted self-designed reducer. Working with a high-precision stepping motor, uArm Swift Pro minimizes gear gap, improves joint accuracy, and is more compact. The built-in 12-bit magnetic encoder and motor forms instant position feedback, achieving closed-loop control, and improves the accuracy to unprecedented 0.2mm, perfectly performs 3D printing and laser engraving.
Working scope improvement:
uArm Swift Series improves mechanical arm structure and increases working range by 20%, covering the working area of an entire A4 paper.
uArm Swift Series upgrades the main board. We choose Arduino MEGA 2560, which is nearly 10 times larger in the storage space compared to the previous UNO edition.
uArm Swift Series has 4-axis, whether equipped with fixtures or suction head, the end of uArm can freely steer, and the replacement of accessories requires less than 30 seconds.
uArm Swift/uArm Swift Pro have a built-in socket for selected Seeed Grove modules.
uArm Swift Series can be equipped with a smart car, the uCar. uCar is a mobile open-source car, with infrared avoidance, trajectory planning functions.
uArm Swift Series adapts CNC integral forming process, and the whole body is matte black. uArm Swift looks has a more minimalistic design. The aluminum body is light and stable, enhancing the overall rigidity.
Compared with the previous version, uArm Swift series redesigned the base, inserted the mainboard and added power button, function switching button, play button and menu button. The new indicator light shows the current operation mode and status of uArm Swift.
uArm Swift Series support PC + mobile control.
Software upgrade -uArm Studio
uArm Studio is a brand new cross-platform robotic arm control software. It has integrated offline learning, graphical programming and instant control functions, manipulate the robotic arm to finish complex tasks.
Teach & Play Offline Learning Mode
Teach uArm Swift by your own hand to learn move, gripping, dropping, and save them with just a click to replay on Blockly mode. uArm Swift can also sync offline learning data once connected.
Blockly-based graphical programming
Blockly is a web-based visual programming tool, allowing users to program without needing to code The software is designed to be so simple that even even preschool children could create a program easily. Detailed tutorial will be provided for your quick guide and interesting secondary development.
uArm Studio has combined control of keyboard and mouse. Developers may use keyboard hotkeys and mouse simultaneously to control move, gripping, and dropping of the robotic arm, and it supports customize hot keys.
After connect with LeapMotion, users of uArm Swift may use their own hand to control gesture such as move, gripping and dropping etc.
Software upgrade –
Robotic Arm has built-in Bluetooth module, simply connect your smartphone with uArm Play to remote control your uArm Swift or uArm Swift Pro.
Your smartphone can also work as an external actuator, download and run a program from Blockly.
UCS, also known as uArm Creator Studio, which is a open sourced developer tool developed by UFACTORY. UCS has integrated graphical programming and coding, to achieve features such as rapid development, visualize and easy sharing.
With numerous commands of UCS, developers don’t need to construct programming environment.
For programming developers, UCS is a rapid development tool, developers doesn’t need to construct programming environment, any interface of the whole system supports Python script, all variables can be sharing between visual programming and coding which means you don’t need to copy setting each time.
Built-in Robotic Vision
UCS has integrated complex robotic vision function, just need to connect with the camera, so the uArm can “see” and adapt to different environment.
The camera can instantly locate, memorize, recognize and track 3D space position of objects.
Every creator will be able to save their own work as .task file format through the UCS programming, and it supports one click sharing to the official website of UFACTORY or Reddit Community, copying scenario in just one click on other robotic arms.
The uArm Swift Pro is a “Open Sourced” design concept with more freedom, simplicity, and functions. This is a whole new open platform came from developers, back to developers, and still that Open Source Robotic Arm. We just can’t wait to become your comprehensive desktop assistant!
I just received this message from Danni, creator of the 8Bit game „The Mystery of Robot Planet“:
The Mystery of Robot Planet is an 8bit inspired adventure-puzzle game for Windows, OS X and Linux scheduled for release in 2018. Visually inspired by early Pokemon games and mechanically based on other adventure-puzzle games such as Monkey Island and Beneath a Steel Sky, the game follows the player character, Ivan, on his quest to become a Marine and save the Princess!
With many vibrant locations, planets and separate endings depending on choices made throughout the game, The Mystery of Robot Planet aims to be a fun, unique and immersive experience for those who crave the puzzle-solving goodness of the early 90s point and click adventure games.
Vienna, Austria, Sept. 20, 2016 — The Vienna-based hardware startup Robo Wunderkind, which develops modular programmable robots for young children, announced today a $500,000 funding round with participation fromArkley VC as lead investor, business angel Juergen Habichler, and the Austrian Federal Promotional Bank (AWS). The funding will go into the widening of their retail reach and the expansion into new markets. The plan is to build a worldwide distribution system and to give young customers from everywhere a chance to learn coding and robotics in a fun and simple way.
The startup already raised $250,000 from backers from 58 countries on Kickstarter in October 2015 and by now collaborated with more than 50 schools around the globe to bring Robo Wunderkind to the classroom. Its vision is to revolutionize the way children interact with technologies through developing educational hardware and software products.
Piotr Wasowski, Managing Partner of Arkley VC:
“I expect Robo Wunderkind to transform how our kids interact with technology. Even very young children will be able to learn the basic principles of programming, which are vital for their future careers and for understanding the world around them.”
Juergen Habichler, Business Angel:
“Robo Wunderkind is the future of education. I have been looking for a long time to find a visionary team, which combines robotics with education. I strongly believe that Robo Wunderkind has the potential to become the education platform for kids, students as well as adults.“
Today, the startup is also announcing its new application to remote control electronic devices: the Robo Play App. Its simple programming interface will allow users to easily create personalized virtual dashboards to control the robots they will build with Robo Wunderkind modules, remotely via Bluetooth or Wifi. In the next step, the team is going to make the Robo Play App compatible with other Internet of Things (IoT) devices, such as cameras, lights, motion and light sensors.
Rustem Akishbekov, co-founder and CEO at Robo Wunderkind:
“In the beginning, we wanted to create an interface that will allow even a 5-year old to control our robotics kit. Eventually, we created a platform that will allow us to expand our target audience and reach older users. With our app, everyone will be able to control their IoT devices with the help of a very intuitive and customizable app. The way our robots prepare young kids for the digital world of the 21st century, our app will open the world of IoT devices to everyone.”
Yuri Levin, Chief Design Officer:
“With the help of our user-friendly and intuitive design, we are making interaction with IoT devices seamless and accessible for the wider audience.”
Robo Play App is free and will work on both Android and iOS devices. It will be compatible with all Robo Wunderkind kits, which are already available for pre-orders on their website with shipping planned for later this year.
About Robo Wunderkind
Robo Wunderkind was founded by Rustem Akishbekov, who brought Anna Iarotska and Yuri Levin on board in 2013. The company is based in Vienna, Austria, and maintains an office in Shenzhen, China. In the last three years, the founders have gathered a team of passionate engineers and designers dedicated to the vision of making coding and robotics accessible to everyone. Their first product is an educational robot that syncs with intuitive mobile applications to help children understand the basics of programming. Robo Wunderkind was part of the world’s first and largest hardware accelerator HAX in 2014 and Finalist of TechCrunch Disrupt SF Startup Battlefield in 2015.
It’s no secret how exciting the trend of makerspaces are for schools. While this movement was started quite some time ago, it seems to have gained particularly great momentum in the past 5 years.
Built on the idea of ‘constructionism’, makerspaces are a very obviously translated idea, where a space is dedicated within a school or educational facility for students to create and ‘make’ things. There is shared resources and networking that takes place and provides a different structure of learning for students. Ranging from woodworks to robotics, these spaces are extremely important in fostering creativity and problem solving in students.
Where Will Makerspaces Work Best?
Makerspaces also range from elementary schools to college campuses, so their versatility is extremely useful.
“….certain materials and tools are emblematic of makerspaces, such as microcontrollers called arduinos and 3D printers, valuable for fast prototyping. As the notion of providing space for project design and construction has caught on in education, such places have acquired other accoutrements, from paints and easels and impromptu stage sets to cooktops and candy molds. Used by students, faculty, and staff, makerspaces have become arenas for informal, project-driven, self-directed learn- ing, providing workspace to tinker, try out solutions, and hear input from colleagues with similar interests. “
It’s places like these that encourage a different type of learning to take place, perhaps a more ‘open-range’ type of environment that differs from the structure of a classroom being led by a teacher.
Some supplies for a makerspace are less available than others, such as 3D printers and robots.
If you compare sharing a robot amongst a class of 20 students to them all sharing a computer to learn from; you can see how the essence of learning is diluted. The experience is completely different and likely not nearly as effective or beneficial to the students until it’s their “turn” to use the computer.
The same can be said for robotics. We know they are extremely useful for teaching many STEM concepts and early mechanical engineering, and LEGO robots are very popular for schools and competitions but start around $400. For most public schools, one robot may be more than is affordable so to effectively teach an entire class by sharing; the students are not receiving the best quality experience from their class.
Here is another example where the Virtual Robotics Toolkit can provide a solution to hundreds of schools and thousands of students, where each student is able to individually use the simulator. They can build and control their own robots using the exact same controller and concepts as the physical robots. In fact, if they’ve already learned how to use a LEGO EV3 MINDSTORMS or NXT robot, they will seamlessly navigate the VRT.
Pilots use flight simulators to learn to fly for the same reason students can learn robotics with one; costs and training purposes.
If students are given access to the VRT in addition to the makerspace of sharing a physical robot, their skills and overall experience will be greatly enhanced and at a fraction of the cost of a real robot.
It’s a win-win for teachers as well, since they’re able to help their class all get to the same level.
Where can this movement take students and educators?
The Educause article says, “One key demand of a makerspace is that it exist as a physical location where participants have room and opportunity for hands-on work, but as these environments evolve, we may see more virtual participation.”
This is such a great point, because of global networking the opportunities are truly endless. Again, here is a great window of opportunity for the VRT to be a part of your school’s makerspace. The software already encourages users to interact and even compete with other robot enthusiasts across the globe via the internet.
This capability allows students to learn from eachother and share ideas and challenges that they would otherwise not have had the access to.
After the wild success of Makeblock, an educational robot kit series targeting makers and educators, the Shenzhen-based hardware startup Shenzhen Maker Works Technology Co., Ltd expanded its reach and designed the user-friendly smart robot Gemini, which requires no programming knowledge or assembling efforts on users’ behalf.
While standing, Gemini moves like a cute puppy, spreading joy via iridescent LED lights and flashing emoticons, and dancing to music at your command. When Gemini is equipped with a turret and crouches down, however, the robot transforms into a fearless warrior who is ready to combat.
The key to Gemini’s accurate signaling and angular actions lies in the self-balancing technology. With one MPU-6050 3-Axis Accelerometer and Gyro working with STM32 MCU, through real-time analysis of related state parameters, Gemini can minimize the displacement both vertically and horizontally, in a timely manner, and control the angular offset with the utmost accuracy, remaining level with ease.
The waterdrop-shaped, two-wheel, streamlined structure, empowered by the dual encoder motors with high resolution, ensures Gemini’s extraordinary agility and mobility.
Innovative Control Systems
Based on the free iPad app, the robot can perform complex motions and tasks with tap-and-swipe finger movements, tilting techniques (gravity control), and voice control.
Together, the 2.4G and Wi-Fi modules offer seamless and timely communication, instantly transmitting and updating all parties’ data throughout the game.
High-Sensitivity LED Blue Light
Inheriting the signature Makeblock blue LED lighting, Gemini improves the transmission efficiency and undermines unstable performance from the reflection of the sun, which is often encountered by IR light-enabled devices. Overall, Gemini offers users an enhanced interactive experience.
Starting at USD $99.00, the team provides different bundles for buyers. “Our mission is to make an ‘Apple product’ for consumer robot kits,” says the founder and robot hobbyist Jasen Wang.