Tag Archives: software
#437747 High Performance Ornithopter Drone Is ...
The vast majority of drones are rotary-wing systems (like quadrotors), and for good reason: They’re cheap, they’re easy, they scale up and down well, and we’re getting quite good at controlling them, even in very challenging environments. For most applications, though, drones lose out to birds and their flapping wings in almost every way—flapping wings are very efficient, enable astonishing agility, and are much safer, able to make compliant contact with surfaces rather than shredding them like a rotor system does. But flapping wing have their challenges too: Making flapping-wing robots is so much more difficult than just duct taping spinning motors to a frame that, with a few exceptions, we haven’t seen nearly as much improvement as we have in more conventional drones.
In Science Robotics last week, a group of roboticists from Singapore, Australia, China, and Taiwan described a new design for a flapping-wing robot that offers enough thrust and control authority to make stable transitions between aggressive flight modes—like flipping and diving—while also being able to efficiently glide and gently land. While still more complex than a quadrotor in both hardware and software, this ornithopter’s advantages might make it worthwhile.
One reason that making a flapping-wing robot is difficult is because the wings have to move back and forth at high speed while electric motors spin around and around at high speed. This requires a relatively complex transmission system, which (if you don’t do it carefully), leads to weight penalties and a significant loss of efficiency. One particular challenge is that the reciprocating mass of the wings tends to cause the entire robot to flex back and forth, which alternately binds and disengages elements in the transmission system.
The researchers’ new ornithopter design mitigates the flexing problem using hinges and bearings in pairs. Elastic elements also help improve efficiency, and the ornithopter is in fact more efficient with its flapping wings than it would be with a rotary propeller-based propulsion system. Its thrust exceeds its 26-gram mass by 40 percent, which is where much of the aerobatic capability comes from. And one of the most surprising findings of this paper was that flapping-wing robots can actually be more efficient than propeller-based aircraft.
One of the most surprising findings of this paper was that flapping-wing robots can actually be more efficient than propeller-based aircraft
It’s not just thrust that’s a challenge for ornithopters: Control is much more complex as well. Like birds, ornithopters have tails, but unlike birds, they have to rely almost entirely on tail control authority, not having that bird-level of control over fine wing movements. To make an acrobatic level of control possible, the tail control surfaces on this ornithopter are huge—the tail plane area is 35 percent of the wing area. The wings can also provide some assistance in specific circumstances, as by combining tail control inputs with a deliberate stall of the things to allow the ornithopter to execute rapid flips.
With the ability to take off, hover, glide, land softly, maneuver acrobatically, fly quietly, and interact with its environment in a way that’s not (immediately) catastrophic, flapping-wing drones easily offer enough advantages to keep them interesting. Now that ornithopters been shown to be even more efficient than rotorcraft, the researchers plan to focus on autonomy with the goal of moving their robot toward real-world usefulness.
“Efficient flapping wing drone arrests high-speed flight using post-stall soaring,” by Yao-Wei Chin, Jia Ming Kok, Yong-Qiang Zhu, Woei-Leong Chan, Javaan S. Chahl, Boo Cheong Khoo, and Gih-Keong Lau from from Nanyang Technological University in Singapore, National University of Singapore, Defence Science and Technology Group in Canberra, Australia, Qingdao University of Technology in Shandong, China, University of South Australia in Mawson Lakes, and National Chiao Tung University in Hsinchu, Taiwan, was published in Science Robotics. Continue reading
Posted in Human Robots
#437709 iRobot Announces Major Software Update, ...
Since the release of the very first Roomba in 2002, iRobot’s long-term goal has been to deliver cleaner floors in a way that’s effortless and invisible. Which sounds pretty great, right? And arguably, iRobot has managed to do exactly this, with its most recent generation of robot vacuums that make their own maps and empty their own dustbins. For those of us who trust our robots, this is awesome, but iRobot has gradually been realizing that many Roomba users either don’t want this level of autonomy, or aren’t ready for it.
Today, iRobot is announcing a major new update to its app that represents a significant shift of its overall approach to home robot autonomy. Humans are being brought back into the loop through software that tries to learn when, where, and how you clean so that your Roomba can adapt itself to your life rather than the other way around.
To understand why this is such a shift for iRobot, let’s take a very brief look back at how the Roomba interface has evolved over the last couple of decades. The first generation of Roomba had three buttons on it that allowed (or required) the user to select whether the room being vacuumed was small or medium or large in size. iRobot ditched that system one generation later, replacing the room size buttons with one single “clean” button. Programmable scheduling meant that users no longer needed to push any buttons at all, and with Roombas able to find their way back to their docking stations, all you needed to do was empty the dustbin. And with the most recent few generations (the S and i series), the dustbin emptying is also done for you, reducing direct interaction with the robot to once a month or less.
Image: iRobot
iRobot CEO Colin Angle believes that working toward more intelligent human-robot collaboration is “the brave new frontier” of AI. “This whole journey has been earning the right to take this next step, because a robot can’t be responsive if it’s incompetent,” he says. “But thinking that autonomy was the destination was where I was just completely wrong.”
The point that the top-end Roombas are at now reflects a goal that iRobot has been working toward since 2002: With autonomy, scheduling, and the clean base to empty the bin, you can set up your Roomba to vacuum when you’re not home, giving you cleaner floors every single day without you even being aware that the Roomba is hard at work while you’re out. It’s not just hands-off, it’s brain-off. No noise, no fuss, just things being cleaner thanks to the efforts of a robot that does its best to be invisible to you. Personally, I’ve been completely sold on this idea for home robots, and iRobot CEO Colin Angle was as well.
“I probably told you that the perfect Roomba is the Roomba that you never see, you never touch, you just come home everyday and it’s done the right thing,” Angle told us. “But customers don’t want that—they want to be able to control what the robot does. We started to hear this a couple years ago, and it took a while before it sunk in, but it made sense.”
How? Angle compares it to having a human come into your house to clean, but you weren’t allowed to tell them where or when to do their job. Maybe after a while, you’ll build up the amount of trust necessary for that to work, but in the short term, it would likely be frustrating. And people get frustrated with their Roombas for this reason. “The desire to have more control over what the robot does kept coming up, and for me, it required a pretty big shift in my view of what intelligence we were trying to build. Autonomy is not intelligence. We need to do something more.”
That something more, Angle says, is a partnership as opposed to autonomy. It’s an acknowledgement that not everyone has the same level of trust in robots as the people who build them. It’s an understanding that people want to have a feeling of control over their homes, that they have set up the way that they want, and that they’ve been cleaning the way that they want, and a robot shouldn’t just come in and do its own thing.
This change in direction also represents a substantial shift in resources for iRobot, and the company has pivoted two-thirds of its engineering organization to focus on software-based collaborative intelligence rather than hardware.
“Until the robot proves that it knows enough about your home and about the way that you want your home cleaned,” Angle says, “you can’t move forward.” He adds that this is one of those things that seem obvious in retrospect, but even if they’d wanted to address the issue before, they didn’t have the technology to solve the problem. Now they do. “This whole journey has been earning the right to take this next step, because a robot can’t be responsive if it’s incompetent,” Angle says. “But thinking that autonomy was the destination was where I was just completely wrong.”
The previous iteration of the iRobot app (and Roombas themselves) are built around one big fat CLEAN button. The new approach instead tries to figure out in much more detail where the robot should clean, and when, using a mixture of autonomous technology and interaction with the user.
Where to Clean
Knowing where to clean depends on your Roomba having a detailed and accurate map of its environment. For several generations now, Roombas have been using visual mapping and localization (VSLAM) to build persistent maps of your home. These maps have been used to tell the Roomba to clean in specific rooms, but that’s about it. With the new update, Roombas with cameras will be able to recognize some objects and features in your home, including chairs, tables, couches, and even countertops. The robots will use these features to identify where messes tend to happen so that they can focus on those areas—like around the dining room table or along the front of the couch.
We should take a minute here to clarify how the Roomba is using its camera. The original (primary?) purpose of the camera was for VSLAM, where the robot would take photos of your home, downsample them into QR-code-like patterns of light and dark, and then use those (with the assistance of other sensors) to navigate. Now the camera is also being used to take pictures of other stuff around your house to make that map more useful.
Photo: iRobot
The robots will now try to fit into the kinds of cleaning routines that many people already have established. For example, the app may suggest an “after dinner” routine that cleans just around the kitchen and dining room table.
This is done through machine learning using a library of images of common household objects from a floor perspective that iRobot had to develop from scratch. Angle clarified for us that this is all done via a neural net that runs on the robot, and that “no recognizable images are ever stored on the robot or kept, and no images ever leave the robot.” Worst case, if all the data iRobot has about your home gets somehow stolen, the hacker would only know that (for example) your dining room has a table in it and the approximate size and location of that table, because the map iRobot has of your place only stores symbolic representations rather than images.
Another useful new feature is intended to help manage the “evil Roomba places” (as Angle puts it) that every home has that cause Roombas to get stuck. If the place is evil enough that Roomba has to call you for help because it gave up completely, Roomba will now remember, and suggest that either you make some changes or that it stops cleaning there, which seems reasonable.
When to Clean
It turns out that the primary cause of mission failure for Roombas is not that they get stuck or that they run out of battery—it’s user cancellation, usually because the robot is getting in the way or being noisy when you don’t want it to be. “If you kill a Roomba’s job because it annoys you,” points out Angle, “how is that robot being a good partner? I think it’s an epic fail.” Of course, it’s not the robot’s fault, because Roombas only clean when we tell them to, which Angle says is part of the problem. “People actually aren’t very good at making their own schedules—they tend to oversimplify, and not think through what their schedules are actually about, which leads to lots of [figurative] Roomba death.”
To help you figure out when the robot should actually be cleaning, the new app will look for patterns in when you ask the robot to clean, and then recommend a schedule based on those patterns. That might mean the robot cleans different areas at different times every day of the week. The app will also make scheduling recommendations that are event-based as well, integrated with other smart home devices. Would you prefer the Roomba to clean every time you leave the house? The app can integrate with your security system (or garage door, or any number of other things) and take care of that for you.
More generally, Roomba will now try to fit into the kinds of cleaning routines that many people already have established. For example, the app may suggest an “after dinner” routine that cleans just around the kitchen and dining room table. The app will also, to some extent, pay attention to the environment and season. It might suggest increasing your vacuuming frequency if pollen counts are especially high, or if it’s pet shedding season and you have a dog. Unfortunately, Roomba isn’t (yet?) capable of recognizing dogs on its own, so the app has to cheat a little bit by asking you some basic questions.
A Smarter App
Image: iRobot
The previous iteration of the iRobot app (and Roombas themselves) are built around one big fat CLEAN button. The new approach instead tries to figure out in much more detail where the robot should clean, and when, using a mixture of autonomous technology and interaction with the user.
The app update, which should be available starting today, is free. The scheduling and recommendations will work on every Roomba model, although for object recognition and anything related to mapping, you’ll need one of the more recent and fancier models with a camera. Future app updates will happen on a more aggressive schedule. Major app releases should happen every six months, with incremental updates happening even more frequently than that.
Angle also told us that overall, this change in direction also represents a substantial shift in resources for iRobot, and the company has pivoted two-thirds of its engineering organization to focus on software-based collaborative intelligence rather than hardware. “It’s not like we’re done doing hardware,” Angle assured us. “But we do think about hardware differently. We view our robots as platforms that have longer life cycles, and each platform will be able to support multiple generations of software. We’ve kind of decoupled robot intelligence from hardware, and that’s a change.”
Angle believes that working toward more intelligent collaboration between humans and robots is “the brave new frontier of artificial intelligence. I expect it to be the frontier for a reasonable amount of time to come,” he adds. “We have a lot of work to do to create the type of easy-to-use experience that consumer robots need.” Continue reading
Posted in Human Robots
#437693 Video Friday: Drone Helps Explore ...
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!):
ICRES 2020 – September 28-29, 2020 – Taipei, Taiwan
AUVSI EXPONENTIAL 2020 – October 5-8, 2020 – [Online Conference]
IROS 2020 – October 25-29, 2020 – Las Vegas, Nev., USA
CYBATHLON 2020 – November 13-14, 2020 – [Online Event]
ICSR 2020 – November 14-16, 2020 – Golden, Colo., USA
Let us know if you have suggestions for next week, and enjoy today's videos.
Clearpath Robotics and Boston Dynamics were obviously destined to partner up with Spot, because Spot 100 percent stole its color scheme from Clearpath, which has a monopoly on yellow and black robots. But seriously, the news here is that thanks to Clearpath, Spot now works seamlessly with ROS.
[ Clearpath Robotics ]
A new video created by Swisscom Ventures highlights a research expedition sponsored by Moncler to explore the deepest ice caves in the world using Flyability’s Elios drone. […] The expedition was sponsored by apparel company Moncler and took place over two weeks in 2018 on the Greenland ice sheet, the second largest body of ice in the world after Antarctica. Research focused on an area about 80 kilometers east of Kangerlussuaq, where scientists wanted to study the movement of water deep underground to better understand the effects of climate change on the melting ice.
[ Flyability ]
Shane Wighton of the “Stuff Made Here” YouTube channel, whose terrifying haircut machine we featured a few months ago, has improved on his robotic basketball hoop. It’s actually more than an improvement: It’s a complete redesign that nearly drove Wighton insane. But the result is pretty cool. It’s fun to watch him building a highly complicated system while always seeking simple and elegant designs for its components.
[ Stuff Made Here ]
SpaceX rockets are really just giant, explosion-powered drones that go into space sometimes. So let's watch more videos of them! This one is sped up, and puts a flight into just a couple of minutes.
[ SpaceX ]
Neato Robotics makes some solid autonomous vacuums, and these incremental upgrades feature improved battery life and better air filters.
[ Neato Robotics ]
A full-scale engineering model of NASA's Perseverance Mars rover now resides in a garage facing the Mars Yard at NASA's Jet Propulsion Laboratory in Southern California.
This vehicle system test bed rover (VSTB) is also known as OPTIMISM, which stands for Operational Perseverance Twin for Integration of Mechanisms and Instruments Sent to Mars. OPTIMISM was built in a warehouselike assembly room near the Mars Yard – an area that simulates the Red Planet's rocky surface. The rover helps the mission test hardware and software before it’s transmitted to the real rover on Mars. OPTIMISM will share the space with the Curiosity rover's twin MAGGIE.
[ JPL ]
Heavy asset industries like shipping, oil and gas, and manufacturing are grounded in repetitive tasks like locating items on large industrial sites — a tedious task that can take as long 45 minutes to find critical items like a forklift in an area that spans the size of multiple football fields. Not only is this work boring, it’s dangerous and inefficient. Robots like Spot, however, love this sort of work.
Spot can provide real-time updates on the location of assets and complete other mundane tasks. In this case, Spot is using software from Cognite to roam the vast shipyard to locate and manage more than 100,000 assets stored across the facility. What used to take humans hours can be managed on an ongoing basis by Spot — leaving employees to focus on more strategic tasks.
[ Cognite ]
The KNEXT Barista system helps high volume premium coffee providers who want to offer artisan coffee specialities in consistent quality.
[ Kuka ]
In this paper, we study this idea of generality in the locomotion domain. We develop a learning framework that can learn sophisticated locomotion behavior for a wide spectrum of legged robots, such as bipeds, tripeds, quadrupeds and hexapods, including wheeled variants. Our learning framework relies on a data-efficient, off-policy multi-task RL algorithm and a small set of reward functions that are semantically identical across robots.
[ DeepMind ]
Thanks Dave!
Even though it seems like the real risk of COVID is catching it from another person, robotics companies are doing what they can with UVC disinfecting systems.
[ BlueBotics ]
Aeditive develop robotic 3D printing solutions for the production of concrete components. At the heart of their production plant are two large robots that cooperate to manufacture the component. The automation technology they build on is a robotic shotcrete process. During this process, they apply concrete layer by layer and thus manufacture complete components. This means that their customers no longer dependent on formwork, which is expensive and time-consuming to create. Instead, their customers can manufacture components directly on a steel pallet without these moulds.
[ Aeditive ]
Something BIG is coming next month from Robotiq!
My guess: an elephant.
[ Robotiq ]
TurtleBot3 is a great little home robot, as long as you have a TurtleBot3-sized home.
[ Robotis ]
How do you calculate the coordinated movements of two robot arms so they can accurately guide a highly flexible tool? ETH researchers have integrated all aspects of the optimisation calculations into an algorithm. The hot-wire cutter will be used, among other things, to develop building blocks for a mortar-free structure.
[ ETH Zurich ]
And now, this.
[ RobotStart ] Continue reading
Posted in Human Robots
#437687 Video Friday: Bittle Is a Palm-Sized ...
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!):
ICRES 2020 – September 28-29, 2020 – Taipei, Taiwan
AUVSI EXPONENTIAL 2020 – October 5-8, 2020 – [Online]
IROS 2020 – October 25-29, 2020 – [Online]
CYBATHLON 2020 – November 13-14, 2020 – [Online]
ICSR 2020 – November 14-16, 2020 – Golden, Colo., USA
Let us know if you have suggestions for next week, and enjoy today's videos.
Rongzhong Li, who is responsible for the adorable robotic cat Nybble, has an updated and even more adorable quadruped that's more robust and agile but only costs around US $200 in kit form on Kickstarter.
Looks like the early bird options are sold out, but a full kit is a $225 pledge, for delivery in December.
[ Kickstarter ]
Thanks Rz!
I still maintain that Stickybot was one of the most elegantly designed robots ever.
[ Stanford ]
With the unpredictable health crisis of COVID-19 continuing to place high demands on hospitals, PAL Robotics have successfully completed testing of their delivery robots in Barcelona hospitals this summer. The TIAGo Delivery and TIAGo Conveyor robots were deployed in Hospital Municipal of Badalona and Hospital Clínic Barcelona following a winning proposal submitted to the European DIH-Hero project. Accerion sensors were integrated onto the TIAGo Delivery Robot and TIAGo Conveyor Robot for use in this project.
[ PAL Robotics ]
Energy Robotics, a leading developer of software solutions for mobile robots used in industrial applications, announced that its remote sensing and inspection solution for Boston Dynamics’s agile mobile robot Spot was successfully deployed at Merck’s thermal exhaust treatment plant at its headquarters in Darmstadt, Germany. Energy Robotics equipped Spot with sensor technology and remote supervision functions to support the inspection mission.
Combining Boston Dynamics’ intuitive controls, robotic intelligence and open interface with Energy Robotics’ control and autonomy software, user interface and encrypted cloud connection, Spot can be taught to autonomously perform a specific inspection round while being supervised remotely from anywhere with internet connectivity. Multiple cameras and industrial sensors enable the robot to find its way around while recording and transmitting information about the facility’s onsite equipment operations.
Spot reads the displays of gauges in its immediate vicinity and can also zoom in on distant objects using an externally-mounted optical zoom lens. In the thermal exhaust treatment facility, for instance, it monitors cooling water levels and notes whether condensation water has accumulated. Outside the facility, Spot monitors pipe bridges for anomalies.
Among the robot’s many abilities, it can detect defects of wires or the temperature of pump components using thermal imaging. The robot was put through its paces on a comprehensive course that tested its ability to handle special challenges such as climbing stairs, scaling embankments and walking over grating.
[ Energy Robotics ]
Thanks Stefan!
Boston Dynamics really should give Dr. Guero an Atlas just to see what he can do with it.
[ DrGuero ]
World's First Socially Distanced Birthday Party: Located in London, the robotic arm was piloted in real time to light the candles on the cake by the founder of Extend Robotics, Chang Liu, who was sat 50 miles away in Reading. Other team members in Manchester and Reading were also able to join in the celebration as the robot was used to accurately light the candles on the birthday cake.
[ Extend Robotics ]
The Robocon in-person competition was canceled this year, but check out Tokyo University's robots in action:
[ Robocon ]
Sphero has managed to pack an entire Sphero into a much smaller sphere.
[ Sphero ]
Squishy Robotics, a small business funded by the National Science Foundation (NSF), is developing mobile sensor robots for use in disaster rescue, remote monitoring, and space exploration. The shape-shifting, mobile, senor robots from UC-Berkeley spin-off Squishy Robotics can be dropped from airplanes or drones and can provide first responders with ground-based situational awareness during fires, hazardous materials (HazMat) release, and natural and man-made disasters.
[ Squishy Robotics ]
Meet Jasper, the small girl with big dreams to FLY. Created by UTS Animal Logic Academy in partnership with the Royal Australian Air Force to encourage girls to soar above the clouds. Jasper was created using a hybrid of traditional animation techniques and technology such as robotics and 3D printing. A KUKA QUANTEC robot is used during the film making to help the Australian Royal Airforce tell their story in a unique way. UTS adapted their High Accurate robot to film consistent paths, creating a video with physical sets and digital characters.
[ AU AF ]
Impressive what the Ghost Robotics V60 can do without any vision sensors on it.
[ Ghost Robotics ]
Is your job moving tiny amounts of liquid around? Would you rather be doing something else? ABB’s YuMi got you.
[ Yumi ]
For his PhD work at the Media Lab, Biomechatronics researcher Roman Stolyarov developed a terrain-adaptive control system for robotic leg prostheses. as a way to help people with amputations feel as able-bodied and mobile as possible, by allowing them to walk seamlessly regardless of the ground terrain.
[ MIT ]
This robot collects data on each cow when she enters to be milked. Milk samples and 3D photos can be taken to monitor the cow’s health status. The Ontario Dairy Research Centre in Elora, Ontario, is leading dairy innovation through education and collaboration. It is a state-of-the-art 175,000 square foot facility for discovery, learning and outreach. This centre is a partnership between the Agricultural Research Institute of Ontario, OMAFRA, the University of Guelph and the Ontario dairy industry.
[ University of Guleph ]
Australia has one of these now, should the rest of us panic?
[ Boeing ]
Daimler and Torc are developing Level 4 automated trucks for the real world. Here is a glimpse into our closed-course testing, routes on public highways in Virginia, and self-driving capabilities development. Our year of collaborating on the future of transportation culminated in the announcement of our new truck testing center in New Mexico.
[ Torc Robotics ] Continue reading
Posted in Human Robots