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Robotic cubes shapeshift in outer space

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.

A method to automatically generate radar-camera datasets for deep learning applications

In recent years, roboticists and computer scientists have been developing a wide range of systems that can detect objects in their environment and navigate it accordingly. Most of these systems are based on machine learning and deep learning algorithms trained on large image datasets.

Team develops fingertip sensitivity for robots

In a paper published on February 23, 2022 in Nature Machine Intelligence, a team of scientists at the Max Planck Institute for Intelligent Systems (MPI-IS) introduce a robust soft haptic sensor named "Insight" that uses computer vision and a deep neural network to accurately estimate where objects come into contact with the sensor and how large the applied forces are. The research project is a significant step toward robots being able to feel their environment as accurately as humans and animals. Like its natural counterpart, the fingertip sensor is very sensitive, robust, and high-resolution.

Tim Chung: DARPA Subterranean Challenge | Sense Think Act Podcast #14

In this episode, Audrow Nash speaks to Tim Chung, Program Manager in the Tactical Technology Office at the Defense Advanced Research Projects Agency (DARPA), on the DARPA Subterranean (SubT) Challenge. The SubT Challenge is a robotics challenge that aims to develop innovative technologies that would augment operations underground. In this conversation, they talk about the motivation of the SubT Challenge, its systems (hardware) and virtual (simulation) challenges, how the resulting technology has been shared with the world, on benchmarking the robotics behaviors in simulation, on the challenge of scoping the SubT Challenge, and on building the final environment for the systems challenge.

Episode Links

Podcast info

Robotic cubes: Self-reconfiguring ElectroVoxels use embedded electromagnets to test applications for space exploration

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.

Artificial emotional intelligence could change senior users’ perceptions of social robots

Socially assistive robots (SARS) are a class of robotic systems specifically designed to help vulnerable or older users to complete everyday activities. In addition to increasing their independence, these robots could stimulate users mentally and offer basic emotional support.

Flying joysticks for better immersion in virtual reality

To interact with elements in the virtual world, common VR headsets usually come with controllers. Users hold these in their hands as they interact with all elements of the virtual user interface. However, the controllers usually do not feel like they look in virtual space. This reduces immersion, i.e., the feeling of how realistic the VR world is perceived.

Automated mining inspection against the odds

Image from Rajant.

Learn how Rajant Corporation, PBE Group, and Australian Droid + Robot – as part of a #MSHA (U.S. Department of Labor)-backed mine safety mission – achieved a historic unmanned underground mine inspection at one of the US’ largest underground room and pillar limestone operations in this comprehensive IM report.

Using ten ADR Explora XL unmanned robots, a Rajant wireless Kinetic Mesh below-ground communication network, and PBE hardware and technology, a horizontal mobile infrastructure distance of 1.7 km was achieved. This allowed the unmanned robots to record high-definition video and LiDAR to create a virtual 3D mine model to assess the condition of the mine, for the deepest remote underground mine inspection in history.

The inspection made it possible for MSHA to conclude within a very short time that it was safe to re-enter the operation and begin remediation efforts, which included allowing mine personnel back into the mine to re-establish power and communications, after which mining was able to recommence quickly at the site.

The project, in many ways, is the ultimate example of necessity breeding innovation. It also showcased the capability of Rajant wireless mesh networks underground to facilitate autonomous mining operations where underground Wi-Fi would not be up to the task.

A reachability-expressive motion planning algorithm to enhance human-robot collaboration

A team of researchers at University of California, Los Angeles (UCLA)'s Center for Vision, Cognition, Learning, and Autonomy (VCLA), led by Prof. Song-Chun Zhu, recently developed an approach that could help to align a human user's assessment of what a robot can do with its true capabilities. This approach, presented in a paper published in IEEE Robotics and Automation Letters, is based on a new algorithm that simultaneously optimizes the physical cost and expressiveness of a robot's motion, to determine how well human observers would estimate its reachable workspace.

A labriform swimming robot to complete missions underwater

Developing robots inspired by animals and other biological systems has become a key research focus for many roboticists worldwide. By artificially reproducing biological mechanisms, these robots could help to automate complex real-world tasks in efficient and reliable ways.
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