Teaching robotics with LEGO Mindstorms

Dylan Evans, Senior Lecturer in Intelligent Autonomous Systems, University of the West of England
As little as four years ago, low-level robotics courses were almost entirely theoretical, because it was too expensive to provide enough equipment for everyone to get direct practical experience. Thanks to the ever-decreasing cost of computing, however, mobile robots are now cheap enough that it is feasible to provide a class of undergraduates with enough equipment to enable all of them to get hands-on experience of building robots. Of the various off-the-shelf kits that may be purchased, my favourite is the LEGO Mindstorms Robotic Invention System.
What is Mindstorms?
Mindstorms is the name that LEGO gives to their range of robotic toys. The basic kit retails for around £170, which may be supplemented with other pieces sold separately. Inside the basic kit is a variety of LEGO components, ranging from the basic building blocks that many adults today remember from their childhood, to gears and axle accessories that can be combined to construct complex steering assemblies. The most important component is the RCX brick, a yellow LEGO block about the size of a cigarette packet that contains a microcontroller chip. Robots of many different shapes and sizes can be constructed by attaching sensors, motors and other components to the RCX brick. Programs can then be written on a computer and downloaded to the chip on the RCX, where they are stored for future use by the robot.
The blurb on the box states that Mindstorms is intended for children aged 12 and above, but this figure on its own is highly misleading. In my capacity as a Science and Engineering Ambassador I have taken Mindstorms into primary schools and witnessed children as young as 7 using it without much difficulty. I have also listened to papers delivered by 60 year-old professors at international scientific conferences in which they describe their use of Mindstorms to conduct advanced research in robotics. Mindstorms is used by a number of universities around the world to teach robotics, and the average age of people owning their own Mindstorms kits is over 30. In other words, Mindstorms approaches the ideal of a 'low-floor, high-ceiling' edutainment system that is simple enough for children to use yet also flexible enough to keep adults engaged.
How do I use Mindstorms in my teaching?
Since September 2004, I have been running a module called 'An Introduction to Robotics' for first-year engineering students enrolled on the new BSc in Robotics that I set up at the University of the West of England. The module comprises 24 one-hour lectures and 24 two-hour workshops. The workshops lead the students through a series of activities designed to take them from scratch to a basic practical knowledge of robot design. Almost all of these activities are based around the LEGO Mindstorms Robotic Invention System, which thereby provides a consistent hardware platform throughout the year.
Although the use of a single hardware platform throughout the course provides a degree of consistency, there is a danger that it might also limit the range of potential learning experiences available to the student. This risk is reduced in this course because the reconfigurable nature of LEGO means that a wide range of different robot bodies can be constructed. This gives Mindstorms a considerable advantage over most other robots used in education, which generally have fixed bodies and are therefore only suitable for teaching programming. With Mindstorms, students can explore the mechanical challenges of building robot bodies as well as the computational challenges of programming robot minds. Mindstorms thus allows students to explore one of the most fascinating and important aspects of robotics - the interaction between the physical design of the robot and its software. Students discover that many problems in robotics can be solved by making small mechanical changes to the body of the robot rather than by introducing complex subroutines into the program.
At the beginning of each workshop, students receive a handout describing the task for that session. They then work in groups of two or three, each with its own Mindstorms kit, to complete the task. My role, as the teacher, is to act as a mobile learning resource, on hand to help groups that require assistance, while not interfering with those who are progressing well on their own. This approach to teaching sits well with theories of learning such as that of Kolb, which emphasise the role of active experimentation and concrete experience. However, the worksheets are not mere task-descriptions, but also encourage students to reflect on what they are doing and to derive more abstract principles from the practical activities they are engaged in.
Mindstorms and constructionism
It does not require an advanced knowledge of pedagogical theory to see that Mindstorms embodies a distinctly constructionist philosophy of learning, one in which great emphasis is placed on the need for students to 'get their hands dirty' by experimenting with things for themselves. In fact, constructionist theories of learning played a direct role in the creation of Mindstorms, which was originally developed by a partnership of the LEGO group and the Massachusetts Institute of Technology (MIT) in the 1980s, and named after a book by an MIT Professor called Seymour Papert. Papert was a long-term collaborator with Jean Piaget, one of the most influential proponents of constructionist approaches to learning.
Not everyone likes to learn by doing. Students differ in their learning styles, with some preferring to 'sit and think' and not to 'poke and see'. A course based around Mindstorms will favour students whose learning styles are more hands-on and may alienate students of a more abstract disposition, but there are several reasons why this is not a grave problem.
Firstly, this course is aimed at precisely those students who are 'good with their hands' but do not excel at the more abstract kinds of exercise which are the staple diet in more traditional engineering courses. Students who like dealing with abstractions can still choose more traditional engineering courses, which tend to put off other students who have difficulty seeing the relevance of the mathematical techniques which are often introduced without any practical context. A traditional course in programming, for example, might start by getting students to write a program that sorts numbers or draws a geometrical pattern. Only much later do students learn to build more useful programs out of the rather dry components they learnt at the start. In this course, by contrast, students write programs to make real robots move around, from the very first week. Not only are the results of their programming more visible and more engaging from the very start, but debugging the program is also much easier when the output is robot behaviour (movement and flashing lights) rather than a series of numbers on a screen.
Secondly, if students who are not 'good with their hands' take this course, they will be forced to develop the manual and visualisation skills that are vital for engineers. With more traditional engineering courses, there has always been a risk that students of a more conceptual bent might be able to pass with flying colours by relying exclusively on their abilities to reason about abstract principles, resulting in graduate engineers who have no feeling for the messy realities of real-world construction.
Mindstorms and abstraction
Although the course does place great emphasis on hands-on experience, it also encourages students to reflect on what they are doing and to derive more abstract principles from the practical activities they are engaged in. This is achieved by means of carefully-designed questions for discussion that will punctuate the task descriptions on the handouts distributed in the workshops. By grounding all these questions in a physical object - a robot that students can constantly manipulate and observe directly - the abstract thinking they encourage is constantly referred back to and tested against the real world. This 'physical anchor' helps students feel safer when venturing into the airy realms of speculation.
Robots are wonderful 'tools for thinking with'. They are 'philosophical toys', embodied thought-experiments, physical prostheses for the mind. They raise all sorts of questions about the nature of machines and animals, and ultimately about ourselves. I take full advantage of the power of robots to help people think through abstract questions by encouraging my students to draw comparisons between the components of their robots and other things such as the organs of animals and the pieces of very different machines. Students may draw inspiration from other machines and from animals when designing their robots, and this in turn may lead them to ask new questions about animals and machines. Their LEGO blocks are transformed into versatile tools for modelling a wide variety of natural and artificial systems. For example, students are encouraged to discover more about how animals find their way back to their nests/burrows/etc and to write programs based on the same principles that enable their robots to navigate.
Robots can also provide an exciting means of teaching what is otherwise usually very dull - the techniques for gathering data about the performance of a machine, and for analysing that data. Such techniques are a fundamental part of any engineer's skillset, but they are usually taught by means of context-free exercises in statistics. By contrast, students on this course are required to use the sensors onboard their robots to collect data about the robot's performance, to find a way of transferring that data to their computers, and to analyse that data in such a way as to derive suggestions for improving the robot. Once again, the robot provides a familiar and meaningful context for an otherwise abstract and disembodied task.
Finally, students are encouraged to think about the differences between the real world and the virtual world by using a range of computer programs that simulate a variety of LEGO robots. Students can program these virtual robots and then watch them run around in the virtual world of the simulation, then download the same program into the real robot and compare its performance to that of the virtual robot. This introduces the students to one of the most interesting debates in contemporary robotics - the relative merits of using computer simulations and real phsyical systems when designing new robots.
Dylan Evans is the author of several popular science books, including Emotion: The Science of Sentiment (Oxford University Press, 2001) and Placebo: The Belief Effect (HarperCollins, 2003). After receiving his PhD in Philosophy from the London School of Economics, he did postdoctoral research in philosophy at King's College London and in robotics at the University of Bath before moving the University of the West of England where he is currently Senior Lecturer in Intelligent Autonomous Systems. He writes regularly for Guardian and the Evening Standard, makes frequent appearances on radio and television, and often gives talks at festivals of science and literature. In 2001 he was voted one of the 20 best young writers in Britain by the Independent on Sunday, and was recently described by the Guardian as 'Alain de Botton in a lab coat'. He also does occasional performances as a DJ at literary events such as the Hay Festival of Literature and the Orange Prize for Fiction.
Dylan EvansFaculty of Computing, Engineering and Mathematical SciencesUniversity of the West of EnglandFrenchay CampusColdharbour LaneBristol BS16 1QY
Bibliography
Baum, D, Gasperi, M, Hempel, R and Villa, L (2000). Extreme Mindstorms: An Advanced Guide to LEGO Mindstorms. New York: Apress
Ferrari, M, Ferrari, G, and Hempel, R (2002). Building Robots with LEGO Mindstorms. Rockland, MA: Syngress Publishing
Wakeman-Linn and J, Perry, A (2002). A Proposal to Incorporate LEGO Mindstorms into an Introduction to Engineering Course. Proceedings of the 2002 ASEE/SEFI/TUB Colloquium