Self-Reconfiguring Robotic Systems & M-Blocks

Self-reconfiguring robots are no longer science fiction. Researchers at MIT are rapidly innovating shape-shifting robotic systems. In the August 2014 issue of Circuit Cellar, MIT researcher Kyle Gilpin presents M-Blocks, which are 50-mm cubic modules capable of controlled self-reconfiguration.

The creation of autonomous machines capable of shape-shifting has been a long-running dream of scientists and engineers. Our enthusiasm for these self-reconfiguring robots is fueled by fantastic science fiction blockbusters, but it stems from the potential that self-reconfiguring robots have to revolutionize our interactions with the world around us.

Source: Kyle Gilpin

Source: Kyle Gilpin

Imagine the convenience of a universal toolkit that can produce even the most specialized tool on demand in a matter of minutes. Alternatively, consider a piece of furniture, or an entire room, that could change its configuration to suit the personal preferences of its occupant. Assembly lines could automatically adapt to new products, and construction scaffolding could build itself while workers sleep. At MIT’s Distributed Robotics Lab, we are working to make these dreams into reality through the development of the M-Blocks.

The M-Blocks are a set of 50-mm cubic modules capable of controlled self-reconfiguration. Each M-Block is an autonomous robot that can not only move independently, but can also magnetically bond with other M-Blocks to form larger reconfigurable systems. When part of a group, each module can climb over and around its neighbors. Our goal is that a set of M-Blocks, dispersed randomly across the ground, could locate one another and then independently move to coalesce into a macro-scale object, like a chair. The modules could then reconfigure themselves into a sphere and collectively roll to a new location. If, in the process, the collective encounters an obstacle (e.g., a set of stairs to be ascended), the sphere could morph into an amorphous collection in which the modules climb over one another to surmount the obstacle.  Once they have reached their final destination, the modules could reassemble into a different object, like a desk.

The M-Blocks move and reconfigure by pivoting about their edges using an inertial actuator. The energy for this actuation comes from a 20,000-RPM flywheel contained within each module. Once the motor speed has stabilized, a servomotor-driven, self-tightening band brake decelerates the flywheel to a complete stop in 15 ms. All of the momentum that had been accumulated in the flywheel is transferred to the frame of the M-Block. Consequently, the module rolls forward from one face to the next, or if the flywheel velocity is high enough, it rapidly shoots across the ground or even jumps several body lengths through the air. (Refer to www.youtube.com/watch?v=mOqjFa4RskA  to watch the cubes move.)

While the M-Blocks are capable of independent movement, their true potential is only realized when many modules operate as a group. Permanent magnets on the outside of each M-Block serve as un-gendered connectors. In particular, each of the 12 edges holds two cylindrical magnets that are captive, but free to rotate, in a semi-enclosing cage. These magnets are polarized through their radii, not through their long axes, so as they rotate, they can present either magnetic pole. The benefit of this arrangement is that as two modules are brought together, the magnets will automatically rotate to attract. Furthermore, as one and then two additional M-Blocks are added to form a 2 × 2 grid, the magnets will always rotate to realign and accommodate the additional modules.

The same cylindrical magnets that bond neighboring M-Blocks together form excellent pivot axes, about which the modules may roll over and around one another. We have shown that the modules can climb vertically over other modules, move horizontally while cantilevered from one side, traverse while suspended from above, and even jump over gaps. The permanent magnet connectors are completely passive, requiring no control and no planning. Because all of the active components of an M-Block are housed internally, the modules could be hermetically sealed, allowing them to operate in extreme environment where other robotic systems may fail.

While we have made significant progress, many exciting challenges remain. In the current generation of modules, there is only a single flywheel, and it is fixed to the module’s frame, so the modules can only move in one direction along a straight line. We are close to publishing a new design that enables the M-Blocks to move in three dimensions, makes the system more robust, and ensures that the modules’ movements are highly repeatable. We also hope to build new varieties of modules that contain cameras, grippers, and other specialized, task-specific tools. Finally, we are developing algorithms that will allow for the coordinated control of large ensembles of hundreds or thousands of modules. With this continued development, we are optimistic that the M-Blocks will be able to solve a variety of practical challenges that are, as of yet, largely untouched by robotics.

Kyle Gilpin

Kyle Gilpin

ABOUT THE AUTHOR

Kyle Gilpin, PhD, is a Postdoctoral Associate in the Distributed Robotics Lab at the Massachusetts Institute of Technology (MIT) where he is collaborating with Professor Daniela Rus and John Romanishin to develop the M-Blocks. Kyle works to improve communication and control in large distributed robotic systems. Before earning his PhD, Kyle spent two years working as a senior electrical engineer at a biomedical device start-up. In addition to working for MIT, he owns a contract design and consulting business, Crosscut Prototypes. His past projects include developing cellular and Wi-Fi devices, real-time image processing systems, reconfigurable sensor nodes, robots with compliant SMA actuators, integrated production test systems, and ultra-low-power sensors.

Circuit Cellar 289 (August 2014) is now available.

The Future of Small Radar Technology

Directing the limited resources of Fighter Command to intercept a fleet of Luftwaffe bombers en route to London or accurately engaging the Imperial Navy at 18,000 yards in the dead of night. This was our grandfather’s radar, the technology that evened the odds in World War II.

This is the combat information center aboard a World War II destroyer with two radar displays.

This is the combat information center aboard a World War II destroyer with two radar displays.

Today there is an insatiable demand for short-range sensors (i.e., small radar technology)—from autonomous vehicles to gaming consoles and consumer devices. State-of-the-art sensors that can provide full 3-D mapping of a small-target scenes include laser radar and time-of-flight (ToF) cameras. Less expensive and less accurate acoustic and infrared devices sense proximity and coarse angle of arrival. The one sensor often overlooked by the both the DIY and professional designer is radar.

However, some are beginning to apply small radar technology to solve the world’s problems. Here are specific examples:

Autonomous vehicles: In 2007, the General Motors and Carnegie Mellon University Tartan Racing team won the Defense Advanced Research Projects Agency (DARPA) Urban Challenge, where autonomous vehicles had to drive through a city in the shortest possible time period. Numerous small radar devices aided in their real-time decision making. Small radar devices will be a key enabling technology for autonomous vehicles—from self-driving automobiles to unmanned aerial drones.

Consumer products: Recently, Massachusetts Institute of Technology (MIT) researchers developed a radar sensor for gaming systems, shown to be capable of detecting gestures and other complex movements inside a room and through interior walls. Expect small radar devices to play a key role in enabling user interface on gaming consoles to smartphones.

The Internet of Things (IoT): Fybr is a technology company that uses small radar sensors to detect the presence of parked automobiles, creating the most accurate parking detection system in the world for smart cities to manage parking and traffic congestion in real time. Small radar sensors will enable the IoT by providing accurate intelligence to data aggregators.

Automotive: Small radar devices are found in mid- to high-priced automobiles in automated cruise control, blind-spot detection, and parking aids. Small radar devices will soon play a key role in automatic braking, obstacle-avoidance systems, and eventually self-driving automobiles, greatly increasing passenger safety.

Through-Wall Imaging: Advances in small radar have numerous possible military applications, including recent MIT work on through-wall imaging of human targets through solid concrete walls. Expect more military uses of small radar technology.

What is taking so long? A tremendous knowledge gap exists between writing the application and emitting, then detecting, scattered microwave fields and understanding the result. Radar was originally developed by physicists who had a deep understanding of electromagnetics and were interested in the theory of microwave propagation and scattering. They created everything from scratch, from antennas to specialized vacuum tubes.

Microwave tube development, for example, required a working knowledge of particle physics. Due to this legacy, radar textbooks are often intensely theoretical. Furthermore, microwave components were very expensive—handmade and gold-plated. Radar was primarily developed by governments and the military, which made high-dollar investments for national security.

Small radar devices such as the RFBeam Microwave K-LC1a radio transceiver cost less than $10 when purchased in quantity.

Small radar devices such as the RFBeam Microwave K-LC1a radio transceiver cost less than $10 when purchased in quantity.

It’s time we make radar a viable option for DIY projects and consumer devices by developing low-cost, easy-to-use, capable technology and bridging the knowledge gap!
Today you can buy small radar sensors for less than $10. Couple this with learning practical radar processing methods, and you can solve a critical sensing problem for your project.

Learn by doing. I created the MIT short-course “Build a Small Radar Sensor,” where students learn about radar by building a device from scratch. Those interested can take the online course for free through MIT Opencourseware or enroll in the five-day MIT Professional Education course.

Dive deeper. My soon-to-be published multimedia book, Small and Short-Range Radar Systems, explains the principles and building of numerous small radar devices and then demonstrates them so readers at all levels can create their own radar devices or learn how to use data from off-the-shelf radar sensors.

This is just the beginning. Soon small radar sensors will be everywhere.

MIT’s Self-Assembling Robots

Calling it a low-tech solution to a high-tech challenge, MIT researchers have received a lot of attention recently for their modular system of self-assembling robot cubes. The video of the so-called M-Blocks in action, which MIT posted earlier this month on YouTube, has also become high profile. A recent tally has the video at nearly 1.5 million views and counting.

 

The text accompanying the video explains how the cubes are able to move around and climb over each other,  jump into the air, and roll across surfaces as they connect in a variety of configurations. And they do all this without any external moving parts. Instead, each M-Block contains a flywheel that can reach speeds of 20,000 rpm. When the flywheel brakes, it imparts angular momentum to the cube.  Precisely placed magnets on every face and edge of each M-Block enable any two cubes to attach to each other.

The simple design holds short- and long-term promise.  According  to an October 4 article by Larry Hardesty of the MIT News Office, it is hoped that the blocks can be miniaturized someday, perhaps to swarming microbots that can self-assemble with a purpose. Even at their current size, further development of the M-Blocks might lead to “armies of mobile cubes” that can help repair bridges and buildings in emergencies, raise scaffolding, reconfigure into heavy equipment or furniture as needed, or head in to environments hostile to humans to diagnose and repair problems, the article suggests.

While it may not rise to “cooperative group behavior,”  the ability of one cube to drag another and influence its alignment is impressive. What could 100 or more of these robots accomplish as MIT researchers continue to develop algorithms to control them?

A prototype of the new modular robot, with its flywheel exposed. (Photo: M. Scott Brauer)

A prototype of the new modular robot, with its interior and flywheel exposed.
(Photo: M. Scott Brauer)

Embedded Sensor Innovation at MIT

During his June 5 keynote address at they 2013 Sensors Expo in Chicago, Joseph Paradiso presented details about some of the innovative embedded sensor-related projects at the MIT Media Lab, where he is the  Director of the Responsive Environments Group. The projects he described ranged from innovative ubiquitous computing installations for monitoring building utilities to a small sensor network that transmits real-time data from a peat bog in rural Massachusetts. Below I detail a few of the projects Paradiso covered in his speech.

DoppleLab

Managed by the Responsive Enviroments group, the DoppelLab is a virtual environment that uses Unity 3D to present real-time data from numerous sensors in MIT Media Lab complex.

The MIT Responsive Environments Group’s DoppleLab

Paradiso explained that the system gathers real-time information and presents it via an interactive browser. Users can monitor room temperature, humidity data, RFID badge movement, and even someone’s Tweets has he moves throughout the complex.

Living Observatory

Paradiso demoed the Living Observatory project, which comprises numerous sensor nodes installed in a peat bog near Plymouth, MA. In addition to transmitting audio from the bog, the installation also logs data such as temperature, humidity, light, barometric pressure, and radio signal strength. The data logs are posted on the project site, where you can also listen to the audio transmission.

The Living Observatory (Source: http://tidmarsh.media.mit.edu/)

GesturesEverywhere

The GesturesEverywhere project provides a real-time data stream about human activity levels within the MIT Media Lab. It provides the following data and more:

  • Activity Level: you can see the Media Labs activity level over a seven-day period.
  • Presence Data: you can see the location of ID tags as people move in the building

The following video is a tracking demo posted on the project site.

The aforementioned projects are just a few of the many cutting-edge developments at the MIT Media Lab. Paradiso said the projects show how far ubiquitous computing technology has come. And they provide a glimpse into the future. For instance, these technologies lend themselves to a variety of building-, environment-, and comfort-related applications.

“In the early days of ubiquitous computing, it was all healthcare,” Paradiso said. “The next frontier is obviously energy.”