Researchers at MIT have made significant steps toward creating robots that could practically and economically assemble nearly anything, including things much larger than themselves, from vehicles to buildings to larger robots. The new system involves large, usable structures built from an array of tiny identical subunits called voxels (the volumetric equivalent of a 2-D pixel). Courtesy of the researchers.

By David L. Chandler

Researchers at MIT have made significant steps toward creating robots that could practically and economically assemble nearly anything, including things much larger than themselves, from vehicles to buildings to larger robots.

The new work, from MIT’s Center for Bits and Atoms (CBA), builds on years of research, including recent studies demonstrating that objects such as a deformable airplane wing and a functional racing car could be assembled from tiny identical lightweight pieces — and that robotic devices could be built to carry out some of this assembly work. Now, the team has shown that both the assembler bots and the components of the structure being built can all be made of the same subunits, and the robots can move independently in large numbers to accomplish large-scale assemblies quickly.

The new work is reported in the journal Nature Communications Engineering, in a paper by CBA doctoral student Amira Abdel-Rahman, Professor and CBA Director Neil Gershenfeld, and three others.

A fully autonomous self-replicating robot assembly system capable of both assembling larger structures, including larger robots, and planning the best construction sequence is still years away, Gershenfeld says. But the new work makes important strides toward that goal, including working out the complex tasks of when to build more robots and how big to make them, as well as how to organize swarms of bots of different sizes to build a structure efficiently without crashing into each other.

As in previous experiments, the new system involves large, usable structures built from an array of tiny identical subunits called voxels (the volumetric equivalent of a 2-D pixel). But while earlier voxels were purely mechanical structural pieces, the team has now developed complex voxels that each can carry both power and data from one unit to the next. This could enable the building of structures that can not only bear loads but also carry out work, such as lifting, moving and manipulating materials — including the voxels themselves.

“When we’re building these structures, you have to build in intelligence,” Gershenfeld says. While earlier versions of assembler bots were connected by bundles of wires to their power source and control systems, “what emerged was the idea of structural electronics — of making voxels that transmit power and data as well as force.” Looking at the new system in operation, he points out, “There’s no wires. There’s just the structure.”

The robots themselves consist of a string of several voxels joined end-to-end. These can grab another voxel using attachment points on one end, then move inchworm-like to the desired position, where the voxel can be attached to the growing structure and released there.

Gershenfeld explains that while the earlier system demonstrated by members of his group could in principle build arbitrarily large structures, as the size of those structures reached a certain point in relation to the size of the assembler robot, the process would become increasingly inefficient because of the ever-longer paths each bot would have to travel to bring each piece to its destination. At that point, with the new system, the bots could decide it was time to build a larger version of themselves that could reach longer distances and reduce the travel time. An even bigger structure might require yet another such step, with the new larger robots creating yet larger ones, while parts of a structure that include lots of fine detail may require more of the smallest robots.

Credit: Amira Abdel-Rahman/MIT Center for Bits and Atoms

As these robotic devices work on assembling something, Abdel-Rahman says, they face choices at every step along the way: “It could build a structure, or it could build another robot of the same size, or it could build a bigger robot.” Part of the work the researchers have been focusing on is creating the algorithms for such decision-making.

“For example, if you want to build a cone or a half-sphere,” she says, “how do you start the path planning, and how do you divide this shape” into different areas that different bots can work on? The software they developed allows someone to input a shape and get an output that shows where to place the first block, and each one after that, based on the distances that need to be traversed.

There are thousands of papers published on route-planning for robots, Gershenfeld says. “But the step after that, of the robot having to make the decision to build another robot or a different kind of robot — that’s new. There’s really nothing prior on that.”

While the experimental system can carry out the assembly and includes the power and data links, in the current versions the connectors between the tiny subunits are not strong enough to bear the necessary loads. The team, including graduate student Miana Smith, is now focusing on developing stronger connectors. “These robots can walk and can place parts,” Gershenfeld says, “but we are almost — but not quite — at the point where one of these robots makes another one and it walks away. And that’s down to fine-tuning of things, like the force of actuators and the strength of joints. … But it’s far enough along that these are the parts that will lead to it.”

Ultimately, such systems might be used to construct a wide variety of large, high-value structures. For example, currently the way airplanes are built involves huge factories with gantries much larger than the components they build, and then “when you make a jumbo jet, you need jumbo jets to carry the parts of the jumbo jet to make it,” Gershenfeld says. With a system like this built up from tiny components assembled by tiny robots, “The final assembly of the airplane is the only assembly.”

Similarly, in producing a new car, “you can spend a year on tooling” before the first car gets actually built, he says. The new system would bypass that whole process. Such potential efficiencies are why Gershenfeld and his students have been working closely with car companies, aviation companies, and NASA. But even the relatively low-tech building construction industry could potentially also benefit.

While there has been increasing interest in 3-D-printed houses, today those require printing machinery as large or larger than the house being built. Again, the potential for such structures to instead be assembled by swarms of tiny robots could provide benefits. And the Defense Advanced Research Projects Agency is also interested in the work for the possibility of building structures for coastal protection against erosion and sea level rise.

The new study shows that both the assembler bots and the components of the structure being built can all be made of the same subunits, and the robots can move independently in large numbers to accomplish large-scale assemblies quickly. Courtesy of the researchers.

Aaron Becker, an associate professor of electrical and computer engineering at the University of Houston, who was not associated with this research, calls this paper “a home run — [offering] an innovative hardware system, a new way to think about scaling a swarm, and rigorous algorithms.”

Becker adds: “This paper examines a critical area of reconfigurable systems: how to quickly scale up a robotic workforce and use it to efficiently assemble materials into a desired structure. … This is the first work I’ve seen that attacks the problem from a radically new perspective — using a raw set of robot parts to build a suite of robots whose sizes are optimized to build the desired structure (and other robots) as fast as possible.”

The research team also included MIT-CBA student Benjamin Jenett and Christopher Cameron, who is now at the U.S. Army Research Laboratory. The work was supported by NASA, the U.S. Army Research Laboratory, and CBA consortia funding.

• PAPER – Self-replicating hierarchical modular robotic swarms. Amira Abdel-Rahman, Christopher Cameron, Benjamin Jenett, Miana Smith, and Neil Gershenfeld. Commun Eng 1, 35 (2022). https://doi.org/10.1038/s44172-022-00034-3

With just a random disturbance that energizes the cubes, they selectively self-assemble into a larger block. Photos courtesy of MIT CSAIL.

By Rachel Gordon | MIT CSAIL

While automated manufacturing is ubiquitous today, it was once a nascent field birthed by inventors such as Oliver Evans, who is credited with creating the first fully automated industrial process, in flour mill he built and gradually automated in the late 1700s. The processes for creating automated structures or machines are still very top-down, requiring humans, factories, or robots to do the assembling and making. 

However, the way nature does assembly is ubiquitously bottom-up; animals and plants are self-assembled at a cellular level, relying on proteins to self-fold into target geometries that encode all the different functions that keep us ticking. For a more bio-inspired, bottom-up approach to assembly, then, human-architected materials need to do better on their own. Making them scalable, selective, and reprogrammable in a way that could mimic nature’s versatility means some teething problems, though. 

Now, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have attempted to get over these growing pains with a new method: introducing magnetically reprogrammable materials that they coat different parts with — like robotic cubes — to let them self-assemble. Key to their process is a way to make these magnetic programs highly selective about what they connect with, enabling robust self-assembly into specific shapes and chosen configurations. 

The soft magnetic material coating the researchers used, sourced from inexpensive refrigerator magnets, endows each of the cubes they built with a magnetic signature on each of its faces. The signatures ensure that each face is selectively attractive to only one other face from all the other cubes, in both translation and rotation. All of the cubes — which run for about 23 cents — can be magnetically programmed at a very fine resolution. Once they’re tossed into a water tank (they used eight cubes for a demo), with a totally random disturbance — you could even just shake them in a box — they’ll bump into each other. If they meet the wrong mate, they’ll drop off, but if they find their suitable mate, they’ll attach. 

An analogy would be to think of a set of furniture parts that you need to assemble into a chair. Traditionally, you’d need a set of instructions to manually assemble parts into a chair (a top-down approach), but using the researchers’ method, these same parts, once programmed magnetically, would self-assemble into the chair using just a random disturbance that makes them collide. Without the signatures they generate, however, the chair would assemble with its legs in the wrong places.

“This work is a step forward in terms of the resolution, cost, and efficacy with which we can self-assemble particular structures,” says Martin Nisser, a PhD student in MIT’s Department of Electrical Engineering and Computer Science (EECS), an affiliate of CSAIL, and the lead author on a new paper about the system. “Prior work in self-assembly has typically required individual parts to be geometrically dissimilar, just like puzzle pieces, which requires individual fabrication of all the parts. Using magnetic programs, however, we can bulk-manufacture homogeneous parts and program them to acquire specific target structures, and importantly, reprogram them to acquire new shapes later on without having to refabricate the parts anew.” 

Using the team’s magnetic plotting machine, one can stick a cube back in the plotter and reprogram it. Every time the plotter touches the material, it creates either a “north”- or “south”-oriented magnetic pixel on the cube’s soft magnetic coating, letting the cubes be repurposed to assemble new target shapes when required. Before plotting, a search algorithm checks each signature for mutual compatibility with all previously programmed signatures to ensure they are selective enough for successful self-assembly.

With self-assembly, you can go the passive or active route. With active assembly, robotic parts modulate their behavior online to locate, position, and bond to their neighbors, and each module needs to be embedded with hardware for the computation, sensing, and actuation required to self-assemble themselves. What’s more, a human or computer is needed in the loop to actively control the actuators embedded in each part to make it move. While active assembly has been successful in reconfiguring a variety of robotic systems, the cost and complexity of the electronics and actuators have been a significant barrier to scaling self-assembling hardware up in numbers and down in size. 

With passive methods like these researchers’, there’s no need for embedded actuation and control.

Once programmed and set free under a random disturbance that gives them the energy to collide with one another, they’re on their own to shapeshift, without any guiding intelligence.  

If you want a structure built from hundreds or thousands of parts, like a ladder or bridge, for example, you wouldn’t want to manufacture a million uniquely different parts, or to have to re-manufacture them when you need a second structure assembled.

The trick the team used toward this goal lies in the mathematical description of the magnetic signatures, which describes each signature as a 2D matrix of pixels. These matrices ensure that any magnetically programmed parts that shouldn’t connect will interact to produce just as many pixels in attraction as those in repulsion, letting them remain agnostic to all non-mating parts in both translation and rotation. 

While the system is currently good enough to do self-assembly using a handful of cubes, the team wants to further develop the mathematical descriptions of the signatures. In particular, they want to leverage design heuristics that would enable assembly with very large numbers of cubes, while avoiding computationally expensive search algorithms. 

“Self-assembly processes are ubiquitous in nature, leading to the incredibly complex and beautiful life we see all around us,” says Hod Lipson, the James and Sally Scapa Professor of Innovation at Columbia University, who was not involved in the paper. “But the underpinnings of self-assembly have baffled engineers: How do two proteins destined to join find each other in a soup of billions of other proteins? Lacking the answer, we have been able to self-assemble only relatively simple structures so far, and resort to top-down manufacturing for the rest. This paper goes a long way to answer this question, proposing a new way in which self-assembling building blocks can find each other. Hopefully, this will allow us to begin climbing the ladder of self-assembled complexity.”

Nisser wrote the paper alongside recent EECS graduates Yashaswini Makaram ’21 and Faraz Faruqi SM ’22, both of whom are former CSAIL affiliates; Ryo Suzuki, assistant professor of computer science at the University of Calgary; and MIT associate professor of EECS Stefanie Mueller, who is a CSAIL affiliate. They will present their research at the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022).

• PAPER – Selective Self-Assembly using Re-Programmable Magnetic Pixels. Martin Nisser, Yashaswini Makaram, Faraz Faruqi1 Ryo Suzuki, and Stefanie Mueller.

MIT PhD student Martin Nisser tests self-reconfiguring robot blocks, or ElectroVoxels, in microgravity. Photo: Steve Boxall/ZeroG

By Rachel Gordon | MIT CSAIL

If faced with the choice of sending a swarm of full-sized, distinct robots to space, or a large crew of smaller robotic modules, you might want to enlist the latter. Modular robots, like those depicted in films such as “Big Hero 6,” hold a special type of promise for their self-assembling and reconfiguring abilities. But for all of the ambitious desire for fast, reliable deployment in domains extending to space exploration, search and rescue, and shape-shifting, modular robots built to date are still a little clunky. They’re typically built from a menagerie of large, expensive motors to facilitate movement, calling for a much-needed focus on more scalable architectures — both up in quantity and down in size.

Scientists from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) called on electromagnetism — electromagnetic fields generated by the movement of electric current — to avoid the usual stuffing of bulky and expensive actuators into individual blocks. Instead, they embedded small, easily manufactured, inexpensive electromagnets into the edges of the cubes that repel and attract, allowing the robots to spin and move around each other and rapidly change shape.

The “ElectroVoxels” have a side length of about 60 millimeters, and the magnets consist of ferrite core (they look like little black tubes) wrapped with copper wire, totaling a whopping cost of just 60 cents. Inside each cube are tiny printed circuit boards and electronics that send current through the right electromagnet in the right direction.

Unlike traditional hinges that require mechanical attachments between two elements, ElectroVoxels are completely wireless, making it much easier to maintain and manufacture for a large-scale system.

ElectroVoxels are robotic cubes that can reconfigure using electromagnets. The cubes don’t need motors or propellant to move, and can operate in microgravity.

To better visualize what a bunch of blocks would look like while interacting, the scientists used a software planner that visualizes reconfigurations and computes the underlying electromagnetic assignments. A user can manipulate up to a thousand cubes with just a few clicks, or use predefined scripts that encode multiple, consecutive rotations. The system really lets the user drive the fate of the blocks, within reason — you can change the speed, highlight the magnets, and display necessary moves to avoid collisions. You can instruct the blocks to take on different shapes (like a chair to a couch, because who needs both?)

The cheap little blocks are particularly auspicious for microgravity environments, where any structure that you want to launch to orbit needs to fit inside the rocket used to launch it. After initial tests on an air table, ElextroVoxels found true weightlessness when tested in a microgravity flight, with the overall impetus of better space exploration tools like propellant-free reconfiguration or changing the inertia properties of a spacecraft.

By leveraging propellant-free actuation, for example, there’s no need to launch extra fuel for reconfiguration, which addresses many of the challenges associated with launch mass and volume. The hope, then, is that this reconfigurability method could aid myriad future space endeavors: augmentation and replacement of space structures over multiple launches, temporary structures to help with spacecraft inspection and astronaut assistance, and (future iterations) of the cubes acting as self-sorting storage containers.

“ElectroVoxels show how to engineer a fully reconfigurable system, and exposes our scientific community to the challenges that need to be tackled to have a fully functional modular robotic system in orbit,” says Dario Izzo, head of the Advanced Concepts Team at the European Space Agency. “This research demonstrates how electromagnetically actuated pivoting cubes are simple to build, operate, and maintain, enabling a flexible, modular and reconfigurable system that can serve as an inspiration to design intelligent components of future exploration missions.”

To make the blocks move, they have to follow a sequence, like little homogeneous Tetris pieces. In this case, there are three steps to the polarization sequence: launch, travel, and catch, with each phase having a traveling cube (for moving), an origin one (where the traveling cube launches), and destination (which catches the traveling cube). Users of the software can specify which cube to pivot in what direction, and the algorithm will automatically compute the sequence and address of electromagnetic assignments required to make that happen (repel, attract, or turn off).

For future work, moving from space to Earth is the natural next step for ElectroVoxels, which would require doing more detailed modeling and optimization of these electromagnets to do reconfiguration against gravity here.

“When building a large, complex structure, you don’t want to be constrained by the availability and expertise of people assembling it, the size of your transportation vehicle, or the adverse environmental conditions of the assembly site. While these axioms hold true on Earth, they compound severely for building things in space,” says MIT CSAIL PhD student Martin Nisser, the lead author on a paper about ElectroVoxels. “If you could have structures that assemble themselves from simple, homogeneous modules, you could eliminate a lot of these problems. So while the potential benefits in space are particularly great, the paradox is that the favorable dynamics provided by microgravity mean some of those problems are actually also easier to solve — in space, even tiny forces can make big things move. By applying this technology to solve real near-term problems in space, we can hopefully incubate the technology for future use on earth too.”

Nisser wrote the paper alongside Leon Cheng and Yashaswini Makaram of MIT CSAIL; Ryo Suzuki, assistant professor of computer science at the University of Calgary; and MIT Professor Stefanie Mueller. They will present the work at the 2022 International Conference on Robotics and Automation. The work was supported, in part, by The MIT Space Exploration Initiative.

• PAPER – ElectroVoxel: Electromagnetically Actuated Pivoting for Scalable Modular Self-Reconfigurable Robots. Martin Nisser, Leon Cheng, Yashaswini Makaram, Ryo Suzuki and Stefanie Mueller. Proceedings of ICRA ’22.

Interesting discussion with Hod Lipson, head of Creative Machines Lab, Columbia University in New York. Can robots be self-aware? Can they design other robots and self-repair? Why should we evolve robots to do tasks that animals do so well? Why don’t we have useful autonomous robots in the real world yet? Find out Hod’s answers to these questions and updates on VoxCAD development for designing and simulation of soft robots in this episode of the IEEE RAS Soft Robotics Podcast.

What’s more, Hod gave his personal advice to roboticists being interviewed for an assistant professorship and to 1st-year robotics PhD students looking for a thesis topic, and he also commented on his approach to the ethical dilemma of military funding scientific research. I hope you enjoy listening to the episode! You can check Hod Lipson’s portfolio here: https://www.hodlipson.com/

You can also listen to this podcast on Spotify and Apple Podcasts, and explore support options on Patreon.

“The set-updemonstrates various techniques that provide a cheaper solution, increased robustness and increased safety for operators”, says Søren Peter Johansen Technology Manager at DTI.

“For example, there is a force-torque sensor in the robot which is used to manoeuvre things carefully into place, and also to increase the confidence of the operators. The force-torque sensor will sense and prevent collisions with people before the built-in safety features of the robot stop the robot arm. Thus, we can also increase safety and confidence by working with collaborative robots”, he says.

Increased effectiveness
Danfoss in Gråsten has tested the robot in connection with the company’s production of frequency converters.

“A frequency converter contains, amongst other things, capacitors assembled in groups of two or four. We have automated this process in that a robot picks up a capacitor and puts it into a fixture. For the capacitor to be correctly placed in the fixture, the electrodes must point in the right direction. Therefore, a camera sees how the electrodes are oriented in the gripper, and orients correctly before it is placed in the fixture”, explains Søren Peter Johansen.

“Then we pick a nut that has to be put on and the robot picks up the socket handle and screws the nut tight. And meanwhile the operator can do something else and thus increases efficiency”, he elaborates.

Three reasons to automate
Peter Lund Andersen, Senior Manufacturing Specialist at Danfoss, says that Danfoss is automating for several reasons:

“It is primarily about work and environmental considerations – better ergonomics and less heavy lifting. We believe that with robots, that can do the work uniformly each time, we can increase the quality of our products while maintaining safety and reducing costs”, he says, adding “The cooperation with DTI gives us the opportunity to come out and try some new things. Some things that aren’t quite mature yet and can’t just be taken off a shelf. That way we are at the forefront with everything.”

If you want to watch more videos, you can explore ROBOTT-NET’s pilot projects on our YouTube-channel.

In this episode, Ron Vanderkley interviews Mark Pivac, Chief Technical Officer and co-founder of FBR (formerly Fastbrick Robotics) about the world’s first end-to-end autonomous bricklaying robot, ‘Hadrian X’. Three years after his first interview, we catch up with Pivac to see how FBR has expanded its operation and chat about their latest commercial prototype, ‘Hadrian X’, as well as the future of the robotic construction industry.

Mark Pivac is the primary inventor of FBR’s automated bricklaying technology. He is an aeronautical and mechanical engineer with over 25 years’ experience working on the development of high technology equipment ranging from lightweight aircraft to heavy off-road equipment. He has 20 years’ experience working with pro/engineer 3D CAD software as well as high-level mathematics, including matrix mathematics, robot transformations and vector mathematics for machine motion. Mark has also worked extensively with design, commissioning and fault finding on servo controlled motion systems achieving very high dynamic performance.

Links

• FBR Website
• Marc Pivac Profile Page
• Hadrian X in action (Video)
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In this episode, Abate interviews Peter Harris from HighRes Biosolutions about automation in the field of drug discovery. At HighRes Biosolutions they are developing modular robotic systems that work alongside scientists to automate laboratory tasks. Because the requirements of each biomedical research laboratory are so varied, the robotic systems are specifically tailored to meet the requirements of each lab.

Peter Harris
Peter Harris is the CEO of HighRes Biosolutions. Prior to HighRes, Peter was VP and Managing Director at Axel Johnson, Inc. He spent most his career as the President & CEO of Cadence, Inc., a high technology medical device manufacturing and engineering firm enabling medical companies to bring better devices to market faster. Peter has been a Visiting Executive Lecturer at the Darden School of Business at the University of Virginia for over 10 years.

Links

• HighRes Biosolutions Website
• “Collaborative robots are redefining lab automation” by Peter Harris
• Peter Harris LinkedIn
• Download mp3 (16.6 MB)
• Subscribe to Robots using iTunes
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Hi, I’m Ben. I was a member of the team that developed a new walking mechanism, TrotBot, that we eventually scaled up to the size of a mini-van (you can read my original post here). Now, at DIYwalkers, I’ve posted plans for TrotBot Ver. 2, designed to handle the weight of the EV3 brick. As you can see in the following videos, we were able to improve TrotBot by borrowing some ideas from a galloping horse.

Just like lunges are more tiring by simply walking, robots with bumpy gaits require more power to walk. This may not be a problem at small scales, but as a robot’s weight increases, smoother gaits are required.  TrotBot Ver. 1 has somewhat of a bumpy gait, but as you can see in my video below, TrotBot’s weight at LEGO-scale is low enough that it walks well:

However, when I added LEGO’s relatively heavy EV3 brick to TrotBot it didn’t perform so well.  To reduce its power requirements, I needed to smooth TrotBot’s gait, which I did by adding active feet that mimic the leg action of a galloping horse.

Background on TrotBot and its Feet

Our goal for TrotBot was to create a walking mechanism capable of walking on rough terrain and areas generally inaccessible to wheeled vehicles, so we designed its linkage to step high. We initially prototyped TrotBot in LEGO with 8 legs.  It walked well enough that we—somewhat naively—thought we could scale it up to mini-van size with only 8 legs.  A team of us spent most of that summer’s boiling hot weekends building our large TrotBot in my garage, only to find, during our first walking test, that too much torque was required to drive the robot up from the gait’s low point.  As we discovered, large walkers should always have at least one foot in contact with the ground at each corner, like how a car’s four wheels are always in contact with the ground. Below, I simulated one corner of a 12 leg version of TrotBot, and as you can see we should have scaled up TrotBot with 12 legs like Theo Jansen’s famous Strandbeest has:

It would have required too many new parts to switch to a 12 leg version of TrotBot, and we didn’t want to start over from scratch, so instead we explored ideas for active feet that could smooth TrotBot’s 8 legged gait.

Using a galloping horse’s gait as inspiration we sought to add some sort of second foot to each leg that would mimic how a horse’s rear then front legs land in pairs. This resulted in the additional linkage that we call TrotBot’s “heel” which increased TrotBot’s foot-contact with the ground by about 10%, reduced how much the feet skidded, and increased the step-height of TrotBot’s rear legs. Shown below is a video comparing TrotBot with these “heels” to a galloping horse:

Next, we explored adding some sort of toe that would push down on the ground as the foot begins to lift, just like how humans use their toes to walk. We installed one of these toe ideas on our large TrotBot but they didn’t smooth the gait enough, and since they were attached to the legs at a fixed angle they tended to catch on obstacles. Catching on obstacles occasionally caused the linkage to lock and gears to grind. In other words, this toe compromised our main goal of creating a mechanism that could walk on rough terrain! Here’s a photo of that toe:

TrotBot’s fixed angle toe

Looking again to a galloping horse for inspiration we started to experiment with linkages that mimicked how horses paw their hooves backward and then keep them folded back as they lift their legs to strike the ground again. We discovered a few options that mimicked this action, and they smoothed the gait by increasing TrotBot’s foot-contact by another 10% while maintaining its high foot-path. I added one of these toe options to TrotBot Ver. 2, and while I couldn’t make a toe with accurate dimensions using LEGO’s integer-based beams, it still smoothes TrotBot’s gait significantly:

Click here for instructions on how to build your own TrotBot Ver. 2!

What do you get when you put together wood and rope? Well according to Plymouth University’s Professor Guido Bugmann: a low-cost, open source, 2 meter tall robot! All buildable for under £2000. The Cheap Arm Project (CHAP) began as an MSc project aimed at developing an affordable mobile robot arm system that could be used by wheelchair users to access daily objects at inaccessible heights or weights (the extreme case being 2 litre bottle).

Now the project has turned open source in the hope of continuing development and gathering more feedback. With the entire hardware and software details available online, with detailed instructions, the team hopes that community members will attempt to construct their own CHAP robot.

While building an entire robot may conventionally seem a complex and expensive undertaking, CHAP stands out with its use of 3D printed parts and wood. In fact, the “under £2000” price tag of required parts is primarily made up of the use six Dynamixel motors, each costing up to £200 and used by the project due to having numerous available during development. With this in mind, future work will look at the use of lower cost motors.

Rather than a robot ‘brain’, CHAP is powered by a human one. To accomplish this, CHAP’s Raspberry Pi was used to host a local web page to enable tele-operation from any connected device, all accessible through a WiFi hotspot also hosted by the Pi. This was an important design choice as it removed the need for platform specific apps and associated costs, simultaneously simplifying deployment and testing.

This was done deliberately to keep the design simple, and to allow users the freedom to interact with their world. Early user-tests discovered that some level of intelligence would be needed to simplify controls. With currently three joints, and three axis available; some steps are needed to automate object interaction (pull requests welcome!).

The next step for CHAP will be refinement of hardware and software; however the very first will be building a community! With full design documents available it is hoped that with support these can be improved and simplified, while simultaneously improving the effectiveness of the software.

Link to the github site can be found here: https://mobile-chap.github.io/Web/

Robotics is becoming more accessible for many people, but the complexities of legged robots mean they remain beyond the reach of most consumers. The complex mechanics, electronics and code algorithms make these robots much more difficult to simply get working. Four legged robots are especially difficult, they might seem very stable but simply lifting a leg up can cause the robot to fall.

QuadBot is an open-source, 3D printed robot that aims to change this.

QuadBot is suitable for makers of any skill level, it works straight out the box, and can be programmed using scratch based blocks. And when you’re ready to explore robotics further, every aspect of QuadBot can be changed, from the mechanical design to individual lines of Arduino code. Once you’ve mastered walking, you can add sensors to the board, and make QuadBot avoid obstacles, follow light and even dance to music!

QuadBot was released on Kickstarter and comes either as a bare bones (3D Print it yourself) kit, or as a full kit. Within the first week, QuadBot reached 100% of the £12,500 goal, and is nearly at £20,000 at the time of writing!

QuadBot is the creation of Jack Scott-Reeve and Josh Elijah, two graduates of Engineering who felt that Robotics Education needed a change. Now that it is funded (and with 5 weeks still left on the campaign), they can focus on improving the product for our early backers. This means adding goals like extra colours, sensor packs and improved learning resources. However, among many Kickstarter campaigns there’s a tendency to overstretch and under deliver, so Elijah and Reeve are letting the product sell on its base features rather than promising massive additions to the design.

Nevertheless, QuadBot has massive future potential for expansion and increased capability, whether using modular design to create QuadBot sensor modules or integrating a Raspberry Pi onto the board to allow Python coding and vision processing.

One emerging market for this technology is robotics in schools. Teaching programming is becoming more common in UK schools, as are products to augment learning like the BBC Microbit. QuadBot could potentially be integrated with existing products like Microbit and the Raspberry Pi, to bring practical robotics into schools. With large distributors like RS Components interested, we could soon see QuadBot being distributed internationally, and with a curriculum to go along with it.

At present it’s hard to say in what direction Elijah and Reeve will go with QuadBot but, with a fully funded Kickstarter already, it’s likely we’ll see many new iterations and designs in the near future!

Click here to visit the QuadBot website.

If you enjoyed this article, you might also be interested in:

• Design, simulate and build a custom drone
• A new quadrupedal robot, the ANYmal
• Make your own Dtto Modular Robot – Assembly instructions (Part 1 of 3)
• mROBerTO: The modular millirobot for swarm behavior studies

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

Paul, a member of the Care-O-bot 4 robot family, has been greeting customers in Saturn-Markt Ingolstadt since the end of October 2016 and directing them towards their desired products. Image: Saturn.

In January 2015, Fraunhofer IPA presented a prototype of the “Care-O-bot 4” service robot. The charming helper is now proving its worth in the real world. “Paul” the robot has been greeting customers in Saturn-Markt Ingolstadt since the end of October 2016 and directing them towards their desired products.

Care-O-bot 4, alias Paul, approaches Saturn customers and welcomes them to the store. If they ask him about a certain product, he accompanies the customer to the department and points them in the direction of the relevant shelf. As he indulges in small talk about the weather, or another subject, Paul turns out to be a most charming contact partner. However, he prefers to leave actual customer service to his human colleagues. Paul is able to call another member of staff for support via “Voice over IP”. Before Paul bids a fond farewell and returns to the store entrance, he still has time to ask for feedback. In this way, he discovers whether customers appreciated the interaction or not. Martin Wild, Chief Digital Officer at Media-Saturn-Holding: “With Paul, we are offering our customers the opportunity to get to know one of the most advanced robots in the world.”

Image: Fraunhofer IPA, Photographer: Rainer Bez (2015)

Modular construction facilitates a wide range of application areas

The interactive robot prototype was originally developed by Fraunhofer IPA as an assistant robot to actively support humans in areas such as the household, hotels, care homes and hospitals. IPA scientists worked together with the design studio Phoenix Design and Schunk over a period of three years to complete the fourth generation of the robot.  While the predecessors of Care-O-bot 4 were used primarily in the development of technological fundamentals from 1989 onwards, the latest version is a modular product family offering elementary commercial solutions for the first time. Fraunhofer IPA is now working with its spin-off company “Unity Robotics” to ensure the solution is suitable for use in various commercial application areas. Saturn is the first customer to make use of the robot platform in real-life scenarios. The project will initially run for six months, with practical findings from customer interactions and employees directly incorporated into the further development of robot technology.

Care-O-bot 4 providing assistance in the kitchen. Image: Phoenix Design 2015

For the assignment with Saturn, the Stuttgart-based scientists supplemented Care-O-bot 4’s software and hardware with additional features. Ulrich Reiser, IPA project manager, explains: “For example, we specified Paul’s navigation, dialog communication and facial expressions. Semvox and Phoenix Design helped implement these changes.” Laser scanners at shin level help with Paul’s orientation. Paul’s front camera and the “Shore” software developed by Fraunhofer IIS allow him to ascertain the mood of the person he is dealing with and express their emotional state. Microphones and cameras for speech and gesture recognition respectively allow Paul to communicate with those around him.

Care-O-bot 4 open for research and industry

Care-O-bot 4 is not only making a positive impression as a retail assistant. With its modular construction and open software interface, the system can be used in many different application areas. It could, for example, conceivably be used as a mobile information kiosk in shops and airports, for pick-up and delivery services in homes and offices, for security applications or as an attraction in a robotics museum. “We retain an interest in ensuring that as many scientists and companies as possible are able to work with the system in order to expand its potential areas of application”, Reiser explains. Within the framework of the Care-O-bot 4 research platform, experts from around the world can further develop the software and hardware components. Together with the spin-off company Unity Robotics, IPA experts are intending to adapt applications to the needs of companies, making Care-O-bot 4 available as a commercial product.

If you enjoyed this article, you might also be interested in:

• Robots Podcast #221: Ori Systems: Robotic Furniture, with Hasier Larrea
• Designing our home service robot from the ground up
• Robot companions are coming into our homes — how human should they be?
• Global and iRobot floor cleaning market
• Robots that may help you in your silver age

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

In this episode, Audrow Nash interviews Hasier Larrea, Founder and CEO of Ori Systems and MSc candidate at the MIT Media Lab, about robotics used to transform personal spaces. Larrea discusses how the world is urbanizing and how new space paradigms are needed to accommodate this shift. He proposes robotic furniture that allows for what is not being used to be hidden, such as a desk or a bed. Larrea discusses the robotic systems, how these systems will be integrated into existing infrastructure, and the future or Ori Systems.

Below is Larrea’s TEDxCambridge talk:

Hasier Larrea
Hasier Larrea is an engineer and designer at the MIT Media Lab. He holds a Bachelors and Masters Degree in Mechanical Engineering. Hasier leads the Architectural Robotics research area at the Media Lab, which focuses on creating a new generation of hyper efficient and responsive urban spaces. His team is developing the robotic tools that allow traditional architectural and furniture elements to transform and intelligently connect to the world around us. His work on the CityHome and CityOffice has been featured in The New York Times, Time, Fast Company, Wired, and TechCrunch among others. His creative and entrepreneurial interests help translate the Lab’s envisioning, inventing, and designing approach into manifesting the ideal smart city from researchers’ minds to the streets of tomorrow.

Links

• Download mp3 (15.4 MB)
• Ori Systems’s homepage
• Subscribe to Robots using iTunes
• Subscribe to Robots using RSS

But what does it mean to describe systems as complex? How do these complex systems differ from the more easily understood ‘modular’ systems that we are familiar with? Vocabulary in this area is often dangerously inconsistent. For example, the terms ’emergence’, ‘complex’, and ‘complicated’ are used differently by different disciplines, and often differently even within the same discipline. This makes it very difficult to understand whether people are really talking about the same thing, and whether the systems being described are different in superficial or profound ways. On the one hand, failing to identify the underlying similarities between different systems (whether modular or complex) results in missed opportunities for sharing knowledge, best practices and methods. On the other hand, failing to identify the underlying differences between different systems results in practices and methods being misapplied. More broadly, many of today’s real-world problems require engineers, designers and policy-makers across all domains to think in terms of complex systems.
To address problems with translating between disciplines, Chih-Chun Chen and Nathan Crilly at the University of Cambridge have produced ‘A primer on the design and science of complex systems’. This introduces complex systems constructs by building them up from basic concepts, and contrasting them with more familiar constructs that are associated with modularity. For example, ’emergence’ can be understood with respect to a breakdown in how a system’s functions are mapped to the structures that perform those functions. Abstract diagrams that are independent of any particular domain are used to represent the constructs that are discussed. These are illustrated with worked examples that make the explanations accessible for those who have no experience with ‘complexity’. The primer is intended to provide both an introduction to complex systems constructs for those new to the topics discussed, and also a basis for cross-domain translations for researchers and practitioners wishing to engage with other fields when addressing the systems problems they are working on.

Being able to communicate unambiguously across disciplines and application areas would greatly expand the space of solutions available to all domains in solving problems currently deemed to be too ‘complex’. As a mature complex systems engineering discipline which is by its nature interdisciplinary, Swarm Robotics will no doubt have much to contribute to – and take from – this endeavour.

If you liked this article, you may also want to read these other articles on swarm robotics:

• mROBerTO: The modular millirobot for swarm behavior studies
• Swarms of precision agriculture robots could help put food on the table
• Machines can learn by simply observing, without being told what to look for
• Raffaello D’Andrea at TED2016: Novel flying machines and swarms of tiny flying robots
• Scaling up underwater swarmbot research from tabletop ‘aquarium’ to the Venice Lagoon (CoCoRo Video #50/52)

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

Developed by a team at the University of Toronto, mROBerTO (milli-ROBot TORonto) is designed for swarm-robotics researchers who might wish to test their collective-behavior algorithms with real physical robots. With just a 16 mm x 16 mm footprint, mROBerTO can be used in a multitude of other miniature robot projects too—its modular design allowing for easy addition or removal of components.

mROBerTOs can determine any nearby robots’ relative distances and bearings by their unique robot IDs (up to 150 mm sensing radius) with the use of modulated IR signals. To achieve this, mROBerTO has an all-around coverage of IR phototransistors and emitters that can receive and send modulated IR signals. Furthermore, mROBerTO is equipped with Bluetooth Smart and ANT Wireless communication capabilities, which allow point-to-point and mesh network communication among robots. As for movement, there are two small motors located at the back of the robot that act as wheels and move the robot in a differential-drive configuration.

mROBerTO modular components. Image: University of Toronto

The majority of swarm robotics research has so far been limited to running virtual simulations for the purpose gathering experimental data. In order to test swarm behavior algorithms in a more realistic setting, we have to use physical robots in an environment where real-world constraints act upon the experiments. However, a swarm will often consist of tens—even hundreds—of robots operating together. So robots should ideally be as small as possible if these swarm algorithms are to be tested in a lab setting with limited work-space. And since we need a large number of these robots for experiments, we should aim to use only off-the-shelf components for easy assembly, production, and maintenance. In addition, certain swarm algorithms may require special sensing capabilities in the swarm robots, requiring modular in-design to allow quick exchanges of processing and sensing hardware. mROBerTO was designed to address these specific issues.

At the moment, there are no commercially available mROBerTOs. The BoM costs approximately 60 USD, and the source files of both the hardware and software can be provided by the developers. mROBerTOs were developed using the Eclipse IDE with SEGGER J-Link programmer/debugger but any integrated development environment that supports ARM GCC can be used to develop on mROBerTOs. For wireless debugging and development purposes, we recommend the user getting an nRF51 or nRF52 development board to wirelessly communicate with mROBerTOs.

mROBerTO was developed by Goldie Nejat, Justin Y. Kim, Tyler Colaco, Zendai Kashino and Beno Benhabib at the University of Toronto, Department of Mechanical Engineering. The latest version of the robot was completed in June 2016 and first featured in 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) as ‘mROBerTO: A Modular Millirobot for Swarm-Behavior Studies’.

If you liked this article, you may also want to read these other articles on swarm robotics:

• Swarms of precision agriculture robots could help put food on the table
• Machines can learn by simply observing, without being told what to look for
• Raffaello D’Andrea at TED2016: Novel flying machines and swarms of tiny flying robots
• Scaling up underwater swarmbot research from tabletop ‘aquarium’ to the Venice Lagoon (CoCoRo Video #50/52)

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

In this episode, Audrow Nash interviews several researchers presenting their work at the Robotics Science and Systems (RSS) 2016 conference in Ann Arbor, Michigan.

Audrow speaks with Gangyuan Jing from Cornell University about modular robotics; Rico Jonschkowski from Technical University of Berlin about lessons from last year’s Amazon picking challenge, which his team won; Matthew Gombolay from MIT about software to help nurses coordinate; and Dorsa Sadigh from UC Berkeley about developing human-like behavior for autonomous cars.

Links:

• Download mp3 (9.7 MB)
• Link to RSS 2016 homepage
• Subscribe to Robots using iTunes
• Subscribe to Robots using RSS

This is the second of two episodes where Audrow Nash interviews several companies at the International Conference for Robotics and Automation (ICRA). ICRA is the IEEE Robotics and Automation Society’s biggest conference and one of the leading international forums for robotics researchers to present their work. The 2016 conference was May 16-21 in Stockholm, Sweden.

Interviews include the following:

Greg Burman, Engineer at iniLabs, explains a novel, high frequency camera that senses differences in illumination at each pixel.

Dave Rollinson, Co-Founder of HEBI robotics, talks about on a modular system for constructing robots.

Tony Prescott, Director of Research at Consequential Robotics, discusses work on a companion robot.

Xavier Carpentier, Phoenix Technologies, on motion tracker used on the International Space Station.

Links:

• Download mp3 (17.4 MB)
• Subscribe to Robots using iTunes
• Subscribe to Robots using RSS

Guest talk in the ShanghAI Lectures, 2010-12-02

Collective systems play very important role on Earth, and we encounter them in all sizes, scales and forms; in biological and technological areas; in ocean, air and on the ground. Examples include viruses, different colloidal systems, nano- and micro-scale particles, huge world of social insects and animals; collective systems in robotics vary from nano- up to large space exploration robots. To some extent, collective systems are ubiquitous. Such a prevalence and diversity and can be explained by several unique properties: scalability, reliability, flexibility, self-developmental capabilities. This guest lecture introduces the area of collective robotics and answers the questions “what and why”. Special attention is given to reconfigurable robotics, we discuses a big vision of “universal modularity” and several ways of its achieving.

https://www.youtube.com/watch?v=R_V_3yN1ZrA

Serge Kernbach is the head of the collective robotics group at the University of Stuttgart, Germany. He graduated in electronic engineering and computer science in 1994. During 1996-1998 he received several research grants, in 2007 his doctoral thesis won the faculty-award as the best dissertation of the year. Since 2004 he has been a coordinator of several European research projects on the field of collective robotics. Serge’s main research interest is focused on artificial collective systems, he is the author and co-author of over 100 articles in international journals and conferences, edited a few books related to robotics. Since 2000 he acquired for IPVS more than 3.5 M€ in different research projects.

The ShanghAI Lectures are a videoconference-based lecture series on Embodied Intelligence, run and organized by Rolf Pfeifer (from 2009 till 2012), Fabio Bonsignorio (since 2013), and me with partners around the world. 

The ShanghAI Lectures have brought us a treasure trove of guest lectures by experts in robotics. You can find the whole series from 2012 here. Now, we’re bringing you the guest lectures you haven’t yet seen from previous years, starting with the first lectures from 2009 and releasing a new guest lecture every Thursday until all the series are complete. Enjoy!

Link to audio file (43:40)

In today’s episode we focus on self-organizing systems in modular and swarm robotics with Radhika Nagpal, director of the Self-Organizing Systems Research Group at the Wyss Institute for Biologically Inspired Engineering at Harvard.

Radhika Nagpal

Whether you’re looking at multicellular organisms or social insects such as ants and termites, nature has found powerful ways to make systems self-organize. In these collectives, individuals that are typically simple, unreliable, and limited, cooperate through local interactions to achieve complex behaviors.

Radhika Nagpal has been building on these principles to make modular and swarm robots that are able to work together in a decentralized manner. She tells us about a self-balancing modular table that is able to adapt to terrain while balancing your cup of coffee. In the TERMES project, robots work together to build the environment in which they evolve, creating the very staircase that will allow them to build a structure. We also look at how her group has made large-scale swarm robotics a reality with the kilobot project and its 1024 quarter-sized robots previously featured on our podcast.

Finally, Nagpal tells us about how her insights in mathematics and the theory of self-organization can also help us learn something about biological systems.

Links:

• Download mp3 (25.8 MB)
• Subscribe to Robots using iTunes
• Subscribe to Robots using RSS
• Radhika Nagpal’s Homepage

Link to audio file (44:00)

In today’s show we hear from our new collaborator, Per Sjoborg who is the founder of Flexibility Envelope, a blog on self-reconfiguring modular robotics. He speaks to Martin Nilsson from the Swedish Institute of Computer Science about his experience in making snake robots and connectors for modular robots.

Martin Nilsson

Martin Nilsson is Associate Professor at the Swedish Institute of Computer Science.

He presents his work on self-reconfigurable modular robots done as part of the DRAGON (Distributed Real-time Autonomously Guided OrgaNisms) project. His snake inspired robot is composed of a set of modules and DRAGON joints that enable the robot to physically connect and disconnect, share energy and communicate. He tells us about challenges in building such a robot, including making smart mechanical docking systems, integrating all the functional requirements of a joint in a single mobile structure, and using Model Predictive Control to generate robot motion.

In his current work, Nilsson is focussing on integration sensor readings to obtain precise motor control. As inspiration, and in collaboration with Neurophysiologists, he looks at how the cerebellum is able to fuse proprioceptive sensing and touch to achieve precise motions in humans.

Links:

• Download mp3 (23.1 MB)
• Subscribe to Robots using iTunes
• Subscribe to Robots using RSS
• Flexibility Envelope Blog
• Martin Nilsson’s homepage

Link to audio file (40:57)

In this episode we dive into the world of programmable matter with Michael Tolley and Jonas Neubert from the Computational Synthesis Laboratory run by Hod Lipson at Cornell University, NY. They present their amazing hardware and control to stochastically assemble matter in fluid.

Michael Tolley

Michael Tolley is finishing his PhD under the supervision of Hod Lipson at Cornell University.

Imagine being able to throw a hand-full of smart matter in a tank full of liquid and then pulling out a ready-to-use wrench once the matter has assembled. As a first step in this direction, Tolley has been looking at how smart cubes can assemble into physical objects in fluids. The interest in using fluid stems from the fact that modules, transported by the flows in their environment, do not need any power or motors. The shapes and latching mechanisms on his cubes, whether on the micro– or centimeter– scale, were smartly designed to enable autonomous alignment and connection. In the end, his approach at building smart matter follows the idea of embodied AI where the intelligence of the robot is embedded in its physical body and its interactions with the environment.

Beyond hardware, Tolley has been looking at controlling such stochastic systems by changing the flows in the tanks to assemble 2D and 3D structures and even repair objects when a part has been broken off. For this purpose, he’s been working on a Programmable Matter Simulator to investigate the possibilities to harness random motion.

Jonas Neubert

Jonas Neubert is also doing his PhD at Hod Lipson’s lab.

As opposed to Tolley, he is looking at making active modules that can compute, connect to neighbors, communicate and open and close valves to direct liquid flows. His setup, presented at ICRA this year is very far from the classical screws and blots used in robotics. Indeed, connections are made by autonomously soldering and desoldering blocks… in liquid. In another original development, valving is done by heating the surrounding fluid which then reacts by becoming a gel and blocking the flow.

Neubert covers all the neat technical developments in his system and the challenges in making electronics that operate in liquid.

Links:

• Download mp3 (23.3 MB)
• Subscribe to Robots using iTunes
• Subscribe to Robots using RSS
• Michael Tolley’s Website
• Jonas Neubert’s Website
• Cornell Computational Synthesis Laboratory

Latest News:
For videos of this week’s Robots news, including the Surena 2 humanoid robot and the prosthetic arm controlled by thought, have a look at the Robots Forum.