Tag Archives: simple
#435664 Swarm Robots Mimic Ant Jaws to Flip and ...
Small robots are appealing because they’re simple, cheap, and it’s easy to make a lot of them. Unfortunately, being simple and cheap means that each robot individually can’t do a whole lot. To make up for this, you can do what insects do—leverage that simplicity and low-cost to just make a huge swarm of simple robots, and together, they can cooperate to carry out relatively complex tasks.
Using insects as an example does set a bit of an unfair expectation for the poor robots, since insects are (let’s be honest) generally smarter and much more versatile than a robot on their scale could ever hope to be. Most robots with insect-like capabilities (like DASH and its family) are really too big and complex to be turned into swarms, because to make a vast amount of small robots, things like motors aren’t going to work because they’re too expensive.
The question, then, is to how to make a swarm of inexpensive small robots with insect-like mobility that don’t need motors to get around, and Jamie Paik’s Reconfigurable Robotics Lab at EPFL has an answer, inspired by trap-jaw ants.
Let’s talk about trap-jaw ants for just a second, because they’re insane. You can read this 2006 paper about them if you’re particularly interested in insane ants (and who isn’t!), but if you just want to hear the insane bit, it’s that trap-jaw ants can fire themselves into the air by biting the ground (!). In just 0.06 millisecond, their half-millimeter long mandibles can close at a top speed of 64 meters per second, which works out to an acceleration of about 100,000 g’s. Biting the ground causes the ant’s head to snap back with a force of 300 times the body weight of the ant itself, which launches the ant upwards. The ants can fly 8 centimeters vertically, and up to 15 cm horizontally—this is a lot, for an ant that’s just a few millimeters long.
Trap-jaw ants can fire themselves into the air by biting the ground, causing the ant’s head to snap back with a force of 300 times the body weight of the ant itself
EPFL’s robots, called Tribots, look nothing at all like trap-jaw ants, which personally I am fine with. They’re about 5 cm tall, weighing 10 grams each, and can be built on a flat sheet, and then folded into a tripod shape, origami-style. Or maybe it’s kirigami, because there’s some cutting involved. The Tribots are fully autonomous, meaning they have onboard power and control, including proximity sensors that allow them to detect objects and avoid them.
Photo: Marc Delachaux/EPFL
EPFL researchers Zhenishbek Zhakypov and Jamie Paik.
Avoiding objects is where the trap-jaw ants come in. Using two different shape-memory actuators (a spring and a latch, similar to how the ant’s jaw works), the Tribots can move around using a bunch of different techniques that can adapt to the terrain that they’re on, including:
Vertical jumping for height
Horizontal jumping for distance
Somersault jumping to clear obstacles
Walking on textured terrain with short hops (called “flic-flac” walking)
Crawling on flat surfaces
Here’s the robot in action:
Tribot’s maximum vertical jump is 14 cm (2.5 times its height), and horizontally it can jump about 23 cm (almost 4 times its length). Tribot is actually quite efficient in these movements, with a cost of transport much lower than similarly-sized robots, on par with insects themselves.
Working together, small groups of Tribots can complete tasks that a single robot couldn’t do alone. One example is pushing a heavy object a set distance. It turns out that you need five Tribots for this task—a leader robot, two worker robots, a monitor robot to measure the distance that the object has been pushed, and then a messenger robot to relay communications around the obstacle.
Image: EPFL
Five Tribots collaborate to move an object to a desired position, using coordination between a leader, two workers, a monitor, and a messenger robot. The leader orders the two worker robots to push the object while the monitor measures the relative position of the object. As the object blocks the two-way link between the leader and the monitor, the messenger maintains the communication link.
The researchers acknowledge that the current version of the hardware is limited in pretty much every way (mobility, sensing, and computation), but it does a reasonable job of demonstrating what’s possible with the concept. The plan going forward is to automate fabrication in order to “enable on-demand, ’push-button-manufactured’” robots.
“Designing minimal and scalable insect-inspired multi-locomotion millirobots,” by Zhenishbek Zhakypov, Kazuaki Mori, Koh Hosoda, and Jamie Paik from EPFL and Osaka University, is published in the current issue of Nature.
[ RRL ] via [ EPFL ] Continue reading
#435640 Video Friday: This Wearable Robotic Tail ...
Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here’s what we have so far (send us your events!):
DARPA SubT Tunnel Circuit – August 15-22, 2019 – Pittsburgh, Pa., USA
CLAWAR 2019 – August 26-28, 2019 – Kuala Lumpur, Malaysia
IEEE Africon 2019 – September 25-27, 2019 – Accra, Ghana
ISRR 2019 – October 6-10, 2019 – Hanoi, Vietnam
Ro-Man 2019 – October 14-18, 2019 – New Delhi, India
Humanoids 2019 – October 15-17, 2019 – Toronto, Canada
ARSO 2019 – October 31-1, 2019 – Beijing, China
ROSCon 2019 – October 31-1, 2019 – Macau
IROS 2019 – November 4-8, 2019 – Macau
Let us know if you have suggestions for next week, and enjoy today’s videos.
Lakshmi Nair from Georgia Tech describes some fascinating research towards robots that can create their own tools, as presented at ICRA this year:
Using a novel capability to reason about shape, function, and attachment of unrelated parts, researchers have for the first time successfully trained an intelligent agent to create basic tools by combining objects.
The breakthrough comes from Georgia Tech’s Robot Autonomy and Interactive Learning (RAIL) research lab and is a significant step toward enabling intelligent agents to devise more advanced tools that could prove useful in hazardous – and potentially life-threatening – environments.
[ Lakshmi Nair ]
Victor Barasuol, from the Dynamic Legged Systems Lab at IIT, wrote in to share some new research on their HyQ quadruped that enables sensorless shin collision detection. This helps the robot navigate unstructured environments, and also mitigates all those painful shin strikes, because ouch.
This will be presented later this month at the International Conference on Climbing and Walking Robots (CLAWAR) in Kuala Lumpur, Malaysia.
[ IIT ]
Thanks Victor!
You used to have a tail, you know—as an embryo, about a month in to your development. All mammals used to have tails, and now we just have useless tailbones, which don’t help us with balancing even a little bit. BRING BACK THE TAIL!
The tail, created by Junichi Nabeshima, Kouta Minamizawa, and MHD Yamen Saraiji from Keio University’s Graduate School of Media Design, was presented at SIGGRAPH 2019 Emerging Technologies.
[ Paper ] via [ Gizmodo ]
The noises in this video are fantastic.
[ ESA ]
Apparently the industrial revolution wasn’t a thorough enough beatdown of human knitting, because the robots are at it again.
[ MIT CSAIL ]
Skydio’s drones just keep getting more and more impressive. Now if only they’d make one that I can afford…
[ Skydio ]
The only thing more fun than watching robots is watching people react to robots.
[ SEER ]
There aren’t any robots in this video, but it’s robotics-related research, and very soothing to watch.
[ Stanford ]
#autonomousicecreamtricycle
In case it wasn’t clear, which it wasn’t, this is a Roboy project. And if you didn’t understand that first video, you definitely won’t understand this second one:
Whatever that t-shirt is at the end (Roboy in sunglasses puking rainbows…?) I need one.
[ Roboy ]
By adding electronics and computation technology to a simple cane that has been around since ancient times, a team of researchers at Columbia Engineering have transformed it into a 21st century robotic device that can provide light-touch assistance in walking to the aged and others with impaired mobility.
The light-touch robotic cane, called CANINE, acts as a cane-like mobile assistant. The device improves the individual’s proprioception, or self-awareness in space, during walking, which in turn improves stability and balance.
[ ROAR Lab ]
During the second field experiment for DARPA’s OFFensive Swarm-Enabled Tactics (OFFSET) program, which took place at Fort Benning, Georgia, teams of autonomous air and ground robots tested tactics on a mission to isolate an urban objective. Similar to the way a firefighting crew establishes a boundary around a burning building, they first identified locations of interest and then created a perimeter around the focal point.
[ DARPA ]
I think there’s a bit of new footage here of Ghost Robotics’ Vision 60 quadruped walking around without sensors on unstructured terrain.
[ Ghost Robotics ]
If you’re as tired of passenger drone hype as I am, there’s absolutely no need to watch this video of NEC’s latest hover test.
[ AP ]
As researchers teach robots to perform more and more complex tasks, the need for realistic simulation environments is growing. Existing techniques for closing the reality gap by approximating real-world physics often require extensive real world data and/or thousands of simulation samples. This paper presents TuneNet, a new machine learning-based method to directly tune the parameters of one model to match another using an iterative residual tuning technique. TuneNet estimates the parameter difference between two models using a single observation from the target and minimal simulation, allowing rapid, accurate and sample-efficient parameter estimation.
The system can be trained via supervised learning over an auto-generated simulated dataset. We show that TuneNet can perform system identification, even when the true parameter values lie well outside the distribution seen during training, and demonstrate that simulators tuned with TuneNet outperform existing techniques for predicting rigid body motion. Finally, we show that our method can estimate real-world parameter values, allowing a robot to perform sim-to-real task transfer on a dynamic manipulation task unseen during training. We are also making a baseline implementation of our code available online.
[ Paper ]
Here’s an update on what GITAI has been up to with their telepresence astronaut-replacement robot.
[ GITAI ]
Curiosity captured this 360-degree panorama of a location on Mars called “Teal Ridge” on June 18, 2019. This location is part of a larger region the rover has been exploring called the “clay-bearing unit” on the side of Mount Sharp, which is inside Gale Crater. The scene is presented with a color adjustment that approximates white balancing to resemble how the rocks and sand would appear under daytime lighting conditions on Earth.
[ MSL ]
Some updates (in English) on ROS from ROSCon France. The first is a keynote from Brian Gerkey:
And this second video is from Omri Ben-Bassat, about how to keep your Anki Vector alive using ROS:
All of the ROSCon FR talks are available on Vimeo.
[ ROSCon FR ] Continue reading
#435621 ANYbotics Introduces Sleek New ANYmal C ...
Quadrupedal robots are making significant advances lately, and just in the past few months we’ve seen Boston Dynamics’ Spot hauling a truck, IIT’s HyQReal pulling a plane, MIT’s MiniCheetah doing backflips, Unitree Robotics’ Laikago towing a van, and Ghost Robotics’ Vision 60 exploring a mine. Robot makers are betting that their four-legged machines will prove useful in a variety of applications in construction, security, delivery, and even at home.
ANYbotics has been working on such applications for years, testing out their ANYmal robot in places where humans typically don’t want to go (like offshore platforms) as well as places where humans really don’t want to go (like sewers), and they have a better idea than most companies what can make quadruped robots successful.
This week, ANYbotics is announcing a completely new quadruped platform, ANYmal C, a major upgrade from the really quite research-y ANYmal B. The new quadruped has been optimized for ruggedness and reliability in industrial environments, with a streamlined body painted a color that lets you know it means business.
ANYmal C’s physical specs are pretty impressive for a production quadruped. It can move at 1 meter per second, manage 20-degree slopes and 45-degree stairs, cross 25-centimeter gaps, and squeeze through passages just 60 centimeters wide. It’s packed with cameras and 3D sensors, including a lidar for 3D mapping and simultaneous localization and mapping (SLAM). All these sensors (along with the vast volume of gait research that’s been done with ANYmal) make this one of the most reliably autonomous quadrupeds out there, with real-time motion planning and obstacle avoidance.
Image: ANYbotics
ANYmal can autonomously attach itself to a cone-shaped docking station to recharge.
ANYmal C is also one of the ruggedest legged robots in existence. The 50-kilogram robot is IP67 rated, meaning that it’s completely impervious to dust and can withstand being submerged in a meter of water for an hour. If it’s submerged for longer than that, you’re absolutely doing something wrong. The robot will run for over 2 hours on battery power, and if that’s not enough endurance, don’t worry, because ANYmal can autonomously impale itself on a weird cone-shaped docking station to recharge.
Photo: ANYbotics
ANYmal C’s sensor payload includes cameras and a lidar for 3D mapping and SLAM.
As far as what ANYmal C is designed to actually do, it’s mostly remote inspection tasks where you need to move around through a relatively complex environment, but where for whatever reason you’d be better off not sending a human. ANYmal C has a sensor payload that gives it lots of visual options, like thermal imaging, and with the ability to handle a 10-kilogram payload, the robot can be adapted to many different environments.
Over the next few months, we’re hoping to see more examples of ANYmal C being deployed to do useful stuff in real-world environments, but for now, we do have a bit more detail from ANYbotics CTO Christian Gehring.
IEEE Spectrum: Can you tell us about the development process for ANYmal C?
Christian Gehring: We tested the previous generation of ANYmal (B) in a broad range of environments over the last few years and gained a lot of insights. Based on our learnings, it became clear that we would have to re-design the robot to meet the requirements of industrial customers in terms of safety, quality, reliability, and lifetime. There were different prototype stages both for the new drives and for single robot assemblies. Apart from electrical tests, we thoroughly tested the thermal control and ingress protection of various subsystems like the depth cameras and actuators.
What can ANYmal C do that the previous version of ANYmal can’t?
ANYmal C was redesigned with a focus on performance increase regarding actuation (new drives), computational power (new hexacore Intel i7 PCs), locomotion and navigation skills, and autonomy (new depth cameras). The new robot additionally features a docking system for autonomous recharging and an inspection payload as an option. The design of ANYmal C is far more integrated than its predecessor, which increases both performance and reliability.
How much of ANYmal C’s development and design was driven by your experience with commercial or industry customers?
Tests (such as the offshore installation with TenneT) and discussions with industry customers were important to get the necessary design input in terms of performance, safety, quality, reliability, and lifetime. Most customers ask for very similar inspection tasks that can be performed with our standard inspection payload and the required software packages. Some are looking for a robot that can also solve some simple manipulation tasks like pushing a button. Overall, most use cases customers have in mind are realistic and achievable, but some are really tough for the robot, like climbing 50° stairs in hot environments of 50°C.
Can you describe how much autonomy you expect ANYmal C to have in industrial or commercial operations?
ANYmal C is primarily developed to perform autonomous routine inspections in industrial environments. This autonomy especially adds value for operations that are difficult to access, as human operation is extremely costly. The robot can naturally also be operated via a remote control and we are working on long-distance remote operation as well.
Do you expect that researchers will be interested in ANYmal C? What research applications could it be useful for?
ANYmal C has been designed to also address the needs of the research community. The robot comes with two powerful hexacore Intel i7 computers and can additionally be equipped with an NVIDIA Jetson Xavier graphics card for learning-based applications. Payload interfaces enable users to easily install and test new sensors. By joining our established ANYmal Research community, researchers get access to simulation tools and software APIs, which boosts their research in various areas like control, machine learning, and navigation.
[ ANYmal C ] Continue reading