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#435804 New AI Systems Are Here to Personalize ...

The narratives about automation and its impact on jobs go from urgent to hopeful and everything in between. Regardless where you land, it’s hard to argue against the idea that technologies like AI and robotics will change our economy and the nature of work in the coming years.

A recent World Economic Forum report noted that some estimates show automation could displace 75 million jobs by 2022, while at the same time creating 133 million new roles. While these estimates predict a net positive for the number of new jobs in the coming decade, displaced workers will need to learn new skills to adapt to the changes. If employees can’t be retrained quickly for jobs in the changing economy, society is likely to face some degree of turmoil.

According to Bryan Talebi, CEO and founder of AI education startup Ahura AI, the same technologies erasing and creating jobs can help workers bridge the gap between the two.

Ahura is developing a product to capture biometric data from adult learners who are using computers to complete online education programs. The goal is to feed this data to an AI system that can modify and adapt their program to optimize for the most effective teaching method.

While the prospect of a computer recording and scrutinizing a learner’s behavioral data will surely generate unease across a society growing more aware and uncomfortable with digital surveillance, some people may look past such discomfort if they experience improved learning outcomes. Users of the system would, in theory, have their own personalized instruction shaped specifically for their unique learning style.

And according to Talebi, their systems are showing some promise.

“Based on our early tests, our technology allows people to learn three to five times faster than traditional education,” Talebi told me.

Currently, Ahura’s system uses the video camera and microphone that come standard on the laptops, tablets, and mobile devices most students are using for their learning programs.

With the computer’s camera Ahura can capture facial movements and micro expressions, measure eye movements, and track fidget score (a measure of how much a student moves while learning). The microphone tracks voice sentiment, and the AI leverages natural language processing to review the learner’s word usage.

From this collection of data Ahura can, according to Talebi, identify the optimal way to deliver content to each individual.

For some users that might mean a video tutorial is the best style of learning, while others may benefit more from some form of experiential or text-based delivery.

“The goal is to alter the format of the content in real time to optimize for attention and retention of the information,” said Talebi. One of Ahura’s main goals is to reduce the frequency with which students switch from their learning program to distractions like social media.

“We can now predict with a 60 percent confidence interval ten seconds before someone switches over to Facebook or Instagram. There’s a lot of work to do to get that up to a 95 percent level, so I don’t want to overstate things, but that’s a promising indication that we can work to cut down on the amount of context-switching by our students,” Talebi said.

Talebi repeatedly mentioned his ambition to leverage the same design principles used by Facebook, Twitter, and others to increase the time users spend on those platforms, but instead use them to design more compelling and even addictive education programs that can compete for attention with social media.

But the notion that Ahura’s system could one day be used to create compelling or addictive education necessarily presses against a set of justified fears surrounding data privacy. Growing anxiety surrounding the potential to misuse user data for social manipulation is widespread.

“Of course there is a real danger, especially because we are collecting so much data about our users which is specifically connected to how they consume content. And because we are looking so closely at the ways people interact with content, it’s incredibly important that this technology never be used for propaganda or to sell things to people,” Talebi tried to assure me.

Unsurprisingly (and worrying), using this AI system to sell products to people is exactly where some investors’ ambitions immediately turn once they learn about the company’s capabilities, according to Talebi. During our discussion Talebi regularly cited the now infamous example of Cambridge Analytica, the political consulting firm hired by the Trump campaign to run a psychographically targeted persuasion campaign on the US population during the most recent presidential election.

“It’s important that we don’t use this technology in those ways. We’re aware that things can go sideways, so we’re hoping to put up guardrails to ensure our system is helping and not harming society,” Talebi said.

Talebi will surely need to take real action on such a claim, but says the company is in the process of identifying a structure for an ethics review board—one that carries significant influence with similar voting authority as the executive team and the regular board.

“Our goal is to build an ethics review board that has teeth, is diverse in both gender and background but also in thought and belief structures. The idea is to have our ethics review panel ensure we’re building things ethically,” he said.

Data privacy appears to be an important issue for Talebi, who occasionally referenced a major competitor in the space based in China. According to a recent article from MIT Tech Review outlining the astonishing growth of AI-powered education platforms in China, data privacy concerns may be less severe there than in the West.

Ahura is currently developing upgrades to an early alpha-stage prototype, but is already capturing data from students from at least one Ivy League school and a variety of other places. Their next step is to roll out a working beta version to over 200,000 users as part of a partnership with an unnamed corporate client who will be measuring the platform’s efficacy against a control group.

Going forward, Ahura hopes to add to its suite of biometric data capture by including things like pupil dilation and facial flushing, heart rate, sleep patterns, or whatever else may give their system an edge in improving learning outcomes.

As information technologies increasingly automate work, it’s likely we’ll also see rapid changes to our labor systems. It’s also looking increasingly likely that those same technologies will be used to improve our ability to give people the right skills when they need them. It may be one way to address the challenges automation is sure to bring.

Image Credit: Gerd Altmann / Pixabay Continue reading

Posted in Human Robots

#435752 T-RHex Is a Hexapod Robot With ...

In Aaron Johnson’s “Robot Design & Experimentation” class at CMU, teams of students have a semester to design and build an experimental robotic system based on a theme. For spring 2019, that theme was “Bioinspired Robotics,” which is definitely one of our favorite kinds of robotics—animals can do all kinds of crazy things, and it’s always a lot of fun watching robots try to match them. They almost never succeed, of course, but even basic imitation can lead to robots with some unique capabilities.

One of the projects from this year’s course, from Team ScienceParrot, is a new version of RHex called T-RHex (pronounced T-Rex, like the dinosaur). T-RHex comes with a tail, but more importantly, it has tiny tapered toes, which help it grip onto rough surfaces like bricks, wood, and concrete. It’s able to climb its way up very steep slopes, and hang from them, relying on its toes to keep itself from falling off.

T-RHex’s toes are called microspines, and we’ve seen them in all kinds of robots. The most famous of these is probably JPL’s LEMUR IIB (which wins on sheer microspine volume), although the concept goes back at least 15 years to Stanford’s SpinyBot. Robots that use microspines to climb tend to be fairly methodical at it, since the microspines have to be engaged and disengaged with care, limiting their non-climbing mobility.

T-RHex manages to perform many of the same sorts of climbing and hanging maneuvers without losing RHex’s ability for quick, efficient wheel-leg (wheg) locomotion.

If you look closely at T-RHex walking in the video, you’ll notice that in its normal forward gait, it’s sort of walking on its ankles, rather than its toes. This means that the microspines aren’t engaged most of the time, so that the robot can use its regular wheg motion to get around. To engage the microspines, the robot moves its whegs backwards, meaning that its tail is arguably coming out of its head. But since all of T-RHex’s capability is mechanical in nature and it has no active sensors, it doesn’t really need a head, so that’s fine.

The highest climbable slope that T-RHex could manage was 55 degrees, meaning that it can’t, yet, conquer vertical walls. The researchers were most surprised by the robot’s ability to cling to surfaces, where it was perfectly happy to hang out on a slope of 135 degrees, which is a 45 degree overhang (!). I have no idea how it would ever reach that kind of position on its own, but it’s nice to know that if it ever does, its spines will keep doing their job.

Photo: CMU

T-RHex uses laser-cut acrylic legs, with the microspines embedded into 3D-printed toes. The tail is needed to prevent the robot from tipping backward.

For more details about the project, we spoke with Team ScienceParrot member (and CMU PhD student) Catherine Pavlov via email.

IEEE Spectrum: We’re used to seeing RHex with compliant, springy legs—how do the new legs affect T-RHex’s mobility?

Catherine Pavlov: There’s some compliance in the legs, though not as much as RHex—this is driven by the use of acrylic, which was chosen for budget/manufacturing reasons. Matching the compliance of RHex with acrylic would have made the tines too weak (since often only a few hold the load of the robot during climbing). It definitely means you can’t use energy storage in the legs the way RHex does, for example when pronking. T-RHex is probably more limited by motor speed in terms of mobility though. We were using some borrowed Dynamixels that didn’t allow for good positioning at high speeds.

How did you design the climbing gait? Why not use the middle legs, and why is the tail necessary?

The gait was a lot of hand-tuning and trial-and-error. We wanted a left/right symmetric gait to enable load sharing among more spines and prevent out-of-plane twisting of the legs. When using all three pairs, you have to have very accurate angular positioning or one leg pair gets pushed off the wall. Since two legs should be able to hold the full robot gait, using the middle legs was hurting more than it was helping, with the middle legs sometimes pushing the rear ones off of the wall.

The tail is needed to prevent the robot from tipping backward and “sitting” on the wall. During static testing we saw the robot tip backward, disengaging the front legs, at around 35 degrees incline. The tail allows us to load the front legs, even when they’re at a shallow angle to the surface. The climbing gait we designed uses the tail to allow the rear legs to fully recirculate without the robot tipping backward.

Photo: CMU

Team ScienceParrot with T-RHex.

What prevents T-RHex from climbing even steeper surfaces?

There are a few limiting factors. One is that the tines of the legs break pretty easily. I think we also need a lighter platform to get fully vertical—we’re going to look at MiniRHex for future work. We’re also not convinced our gait is the best it can be, we can probably get marginal improvements with more tuning, which might be enough.

Can the microspines assist with more dynamic maneuvers?

Dynamic climbing maneuvers? I think that would only be possible on surfaces with very good surface adhesion and very good surface strength, but it’s certainly theoretically possible. The current instance of T-RHex would definitely break if you tried to wall jump though.

What are you working on next?

Our main target is exploring the space of materials for leg fabrication, such as fiberglass, PLA, urethanes, and maybe metallic glass. We think there’s a lot of room for improvement in the leg material and geometry. We’d also like to see MiniRHex equipped with microspines, which will require legs about half the scale of what we built for T-RHex. Longer-term improvements would be the addition of sensors e.g. for wall detection, and a reliable floor-to-wall transition and dynamic gait transitions.

[ T-RHex ] Continue reading

Posted in Human Robots

#435748 Video Friday: This Robot Is Like a ...

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!):

RSS 2019 – June 22-26, 2019 – Freiburg, Germany
Hamlyn Symposium on Medical Robotics – June 23-26, 2019 – London, U.K.
ETH Robotics Summer School – June 27-1, 2019 – Zurich, Switzerland
MARSS 2019 – July 1-5, 2019 – Helsinki, Finland
ICRES 2019 – July 29-30, 2019 – London, U.K.
DARPA SubT Tunnel Circuit – August 15-22, 2019 – Pittsburgh, Pa., USA
Let us know if you have suggestions for next week, and enjoy today’s videos.

It’s been a while since we last spoke to Joe Jones, the inventor of Roomba, about his solar-powered, weed-killing robot, called Tertill, which he was launching as a Kickstarter project. Tertill is now available for purchase (US $300) and is shipping right now.

[ Tertill ]

Usually, we don’t post videos that involve drone use that looks to be either illegal or unsafe. These flights over the protests in Hong Kong are almost certainly both. However, it’s also a unique perspective on the scale of these protests.

[ Team BlackSheep ]

ICYMI: iRobot announced this week that it has acquired Root Robotics.

[ iRobot ]

This Boston Dynamics parody video went viral this week.

The CGI is good but the gratuitous violence—even if it’s against a fake robot—is a bit too much?

This is still our favorite Boston Dynamics parody video:

[ Corridor ]

Biomedical Engineering Department Head Bin He and his team have developed the first-ever successful non-invasive mind-controlled robotic arm to continuously track a computer cursor.

[ CMU ]

Organic chemists, prepare to meet your replacement:

Automated chemical synthesis carries great promises of safety, efficiency and reproducibility for both research and industry laboratories. Current approaches are based on specifically-designed automation systems, which present two major drawbacks: (i) existing apparatus must be modified to be integrated into the automation systems; (ii) such systems are not flexible and would require substantial re-design to handle new reactions or procedures. In this paper, we propose a system based on a robot arm which, by mimicking the motions of human chemists, is able to perform complex chemical reactions without any modifications to the existing setup used by humans. The system is capable of precise liquid handling, mixing, filtering, and is flexible: new skills and procedures could be added with minimum effort. We show that the robot is able to perform a Michael reaction, reaching a yield of 34%, which is comparable to that obtained by a junior chemist (undergraduate student in Chemistry).

[ arXiv ] via [ NTU ]

So yeah, ICRA 2019 was huge and awesome. Here are some brief highlights.

[ Montreal Gazette ]

For about US $5, this drone will deliver raw meat and beer to you if you live on an uninhabited island in Tokyo Bay.

[ Nikkei ]

The Smart Microsystems Lab at Michigan State University has a new version of their Autonomous Surface Craft. It’s autonomous, open source, and awfully hard to sink.

[ SML ]

As drone shows go, this one is pretty good.

[ CCTV ]

Here’s a remote controlled robot shooting stuff with a very large gun.

[ HDT ]

Over a period of three quarters (September 2018 thru May 2019), we’ve had the opportunity to work with five graduating University of Denver students as they brought their idea for a Misty II arm extension to life.

[ Misty Robotics ]

If you wonder how it looks to inspect burners and superheaters of a boiler with an Elios 2, here you are! This inspection was performed by Svenska Elektrod in a peat-fired boiler for Vattenfall in Sweden. Enjoy!

[ Flyability ]

The newest Soft Robotics technology, mGrip mini fingers, made for tight spaces, small packaging, and delicate items, giving limitless opportunities for your applications.

[ Soft Robotics ]

What if legged robots were able to generate dynamic motions in real-time while interacting with a complex environment? Such technology would represent a significant step forward the deployment of legged systems in real world scenarios. This means being able to replace humans in the execution of dangerous tasks and to collaborate with them in industrial applications.

This workshop aims to bring together researchers from all the relevant communities in legged locomotion such as: numerical optimization, machine learning (ML), model predictive control (MPC) and computational geometry in order to chart the most promising methods to address the above-mentioned scientific challenges.

[ Num Opt Wkshp ]

Army researchers teamed with the U.S. Marine Corps to fly and test 3-D printed quadcopter prototypes a the Marine Corps Air Ground Combat Center in 29 Palms, California recently.

[ CCDC ARL ]

Lex Fridman’s Artificial Intelligence podcast featuring Rosalind Picard.

[ AI Podcast ]

In this week’s episode of Robots in Depth, per speaks with Christian Guttmann, executive director of the Nordic AI Artificial Intelligence Institute.

Christian Guttmann talks about AI and wanting to understand intelligence enough to recreate it. Christian has be focusing on AI in healthcare and has recently started to communicate the opportunities and challenges in artificial intelligence to the general public. This is something that the host Per Sjöborg is also very passionate about. We also get to hear about the Nordic AI institute and the work it does to inform all parts of society about AI.

[ Robots in Depth ] Continue reading

Posted in Human Robots

#435738 Boing Goes the Trampoline Robot

There are a handful of quadrupedal robots out there that are highly dynamic, with the ability to run and jump, but those robots tend to be rather expensive and complicated, requiring powerful actuators and legs with elasticity. Boxing Wang, a Ph.D. student in the College of Control Science and Engineering at Zhejiang University in China, contacted us to share a project he’s been working to investigate quadruped jumping with simple, affordable hardware.

“The motivation for this project is quite simple,” Boxing says. “I wanted to study quadrupedal jumping control, but I didn’t have custom-made powerful actuators, and I didn’t want to have to design elastic legs. So I decided to use a trampoline to make a normal servo-driven quadruped robot to jump.”

Boxing and his colleagues had wanted to study quadrupedal running and jumping, so they built this robot with the most powerful servos they had access to: Kondo KRS6003RHV actuators, which have a maximum torque of 6 Nm. After some simple testing, it became clear that the servos were simply not fast or powerful enough to get the robot to jump, and that an elastic element was necessary to store energy to help the robot get off the ground.

“Normally, people would choose elastic legs,” says Boxing. “But nobody in my lab knew for sure how to design them. If we tried making elastic legs and we failed to make the robot jump, we couldn’t be sure whether the problem was the legs or the control algorithms. For hardware, we decided that it’s better to start with something reliable, something that definitely won’t be the source of the problem.”

As it turns out, all you need is a trampoline, an inertial measurement unit (IMU), and little tactile switches on the end of each foot to detect touch-down and lift-off events, and you can do some useful jumping research without a jumping robot. And the trampoline has other benefits as well—because it’s stiffer at the edges than at the center, for example, the robot will tend to center itself on the trampoline, and you get some warning before things go wrong.

“I can’t say that it’s a breakthrough to make a quadruped robot jump on a trampoline,” Boxing tells us. “But I believe this is useful for prototype testing, especially for people who are interested in quadrupedal jumping control but without a suitable robot at hand.”

To learn more about the project, we emailed him some additional questions.

IEEE Spectrum: Where did this idea come from?

Boxing Wang: The idea of the trampoline came while we were drinking milk tea. I don’t know why it came up, maybe someone saw a trampoline in a gym recently. And I don’t remember who proposed it exactly. It was just like someone said it unintentionally. But I realized that a trampoline would be a perfect choice. It’s reliable, easy to buy, and should have a similar dynamic model with the one of jumping with springy legs (we have briefly analyzed this in a paper). So I decided to try the trampoline.

How much do you think you can learn using a quadruped on a trampoline, instead of using a jumping quadruped?

Generally speaking, no contact surfaces are strictly rigid. They all have elasticity. So there are no essential differences between jumping on a trampoline and jumping on a rigid surface. However, using a quadruped on a trampoline can give you more information on how to make use of elasticity to make jumping easier and more efficient. You can use quadruped robots with springy legs to address the same problem, but that usually requires much more time on hardware design.

We prefer to treat the trampoline experiment as a kind of early test for further real jumping quadruped design. Unless you’re interested in designing an acrobatic robot on a trampoline, a real jumping quadruped is probably a more useful application, and that is our ultimate goal. The point of the trampoline tests is to develop the control algorithms first, and to examine the stability of the general hardware structure. Due to the similarity between jumping on a trampoline with rigid legs and jumping on hard surfaces with springy legs, the control algorithms you develop could be transferred to hard-surface jumping robots.

“Unless you’re interested in designing an acrobatic robot on a trampoline, a real jumping quadruped is probably a more useful application, and that is our ultimate goal. The point of the trampoline tests is to develop the control algorithms first, and to examine the stability of the general hardware structure”

Do you think that this idea can be beneficial for other kinds of robotics research?

Yes. For jumping quadrupeds with springy legs, the control algorithms could be first designed through trampoline tests using simple rigid legs. And the hardware design for elastic legs could be accelerated with the help of the control algorithms you design. In addition, we believe our work could be a good example of using a position-control robot to realize dynamic motions such as jumping, or even running.

Unlike other dynamic robots, every active joint in our robot is controlled through commercial position-control servos and not custom torque control motors. Most people don’t think that a position-control robot could perform highly dynamic motions such as jumping, because position-control motors usually mean high a gear ratio and slow response. However, our work indicates that, with the help of elasticity, stable jumping could be realized through position-control servos. So for those who already have a position-control robot at hand, they could explore the potential of their robot through trampoline tests.

Why is teaching a robot to jump important?

There are many scenarios where a jumping robot is needed. For example, a real jumping quadruped could be used to design a running quadruped. Both experience moments when all four legs are in the air, and it is easier to start from jumping and then move to running. Specifically, hopping or pronking can easily transform to bounding if the pitch angle is not strictly controlled. A bounding quadruped is similar to a running rabbit, so for now it can already be called a running quadruped.

To the best of our knowledge, a practical use of jumping quadrupeds could be planet exploration, just like what SpaceBok was designed for. In a low-gravity environment, jumping is more efficient than walking, and it’s easier to jump over obstacles. But if I had a jumping quadruped on Earth, I would teach it to catch a ball that I throw at it by jumping. It would be fantastic!

That would be fantastic.

Since the whole point of the trampoline was to get jumping software up and running with a minimum of hardware, the next step is to add some springy legs to the robot so that the control system the researchers developed can be tested on hard surfaces. They have a journal paper currently under revision, and Boxing Wang is joined as first author by his adviser Chunlin Zhou, undergrads Ziheng Duan and Qichao Zhu, and researchers Jun Wu and Rong Xiong. Continue reading

Posted in Human Robots

#435726 This Is the Most Powerful Robot Arm Ever ...

Last month, engineers at NASA’s Jet Propulsion Laboratory wrapped up the installation of the Mars 2020 rover’s 2.1-meter-long robot arm. This is the most powerful arm ever installed on a Mars rover. Even though the Mars 2020 rover shares much of its design with Curiosity, the new arm was redesigned to be able to do much more complex science, drilling into rocks to collect samples that can be stored for later recovery.

JPL is well known for developing robots that do amazing work in incredibly distant and hostile environments. The Opportunity Mars rover, to name just one example, had a 90-day planned mission but remained operational for 5,498 days in a robot unfriendly place full of dust and wild temperature swings where even the most basic maintenance or repair is utterly impossible. (Its twin rover, Spirit, operated for 2,269 days.)

To learn more about the process behind designing robotic systems that are capable of feats like these, we talked with Matt Robinson, one of the engineers who designed the Mars 2020 rover’s new robot arm.

The Mars 2020 rover (which will be officially named through a public contest which opens this fall) is scheduled to launch in July of 2020, landing in Jezero Crater on February 18, 2021. The overall design is similar to the Mars Science Laboratory (MSL) rover, named Curiosity, which has been exploring Gale Crater on Mars since August 2012, except Mars 2020 will be a bit bigger and capable of doing even more amazing science. It will outweigh Curiosity by about 150 kilograms, but it’s otherwise about the same size, and uses the same type of radioisotope thermoelectric generator for power. Upgraded aluminum wheels will be more durable than Curiosity’s wheels, which have suffered significant wear. Mars 2020 will land on Mars in the same way that Curiosity did, with a mildly insane descent to the surface from a rocket-powered hovering “skycrane.”

Photo: NASA/JPL-Caltech

Last month, engineers at NASA's Jet Propulsion Laboratory install the main robotic arm on the Mars 2020 rover. Measuring 2.1 meters long, the arm will allow the rover to work as a human geologist would: by holding and using science tools with its turret.

Mars 2020 really steps it up when it comes to science. The most interesting new capability (besides serving as the base station for a highly experimental autonomous helicopter) is that the rover will be able to take surface samples of rock and soil, put them into tubes, seal the tubes up, and then cache the tubes on the surface for later retrieval (and potentially return to Earth for analysis). Collecting the samples is the job of a drill on the end of the robot arm that can be equipped with a variety of interchangeable bits, but the arm holds a number of other instruments as well. A “turret” can swap between the drill, a mineral identification sensor suite called SHERLOC, and an X-ray spectrometer and camera called PIXL. Fundamentally, most of Mars 2020’s science work is going to depend on the arm and the hardware that it carries, both in terms of close-up surface investigations and collecting samples for caching.

Matt Robinson is the Deputy Delivery Manager for the Sample Caching System on the Mars 2020 rover, which covers the robotic arm itself, the drill at the end of the arm, and the sample caching system within the body of the rover that manages the samples. Robinson has been at JPL since 2001, and he’s worked on the Mars Phoenix Lander mission as the robotic arm flight software developer and robotic arm test and operations engineer, as well as on Curiosity as the robotic arm test and operations lead engineer.

We spoke with Robinson about how the Mars 2020 arm was designed, and what it’s like to be building robots for exploring other planets.

IEEE Spectrum: How’d you end up working on robots at JPL?

Matt Robinson: When I was a grad student, my focus was on vision-based robotics research, so the kinds of things they do at JPL, or that we do at JPL now, were right within my wheelhouse. One of my advisors in grad school had a former student who was out here at JPL, so that’s how I made the contact. But I was very excited to come to JPL—as a young grad student working in robotics, space robotics was where it’s at.

For a robotics engineer, working in space is kind of the gold standard. You’re working in a challenging environment and you have to be prepared for any time of eventuality that may occur. And when you send your robot out to space, there’s no getting it back.

Once the rover arrives on Mars and you receive pictures back from it operating, there’s no greater feeling. You’ve built something that is now working 200+ million miles away. It’s an awesome experience! I have to pinch myself sometimes with the job I do. Working at JPL on space robotics is the holy grail for a roboticist.

What’s different about designing an arm for a rover that will operate on Mars?

We spent over five years designing, manufacturing, assembling, and testing the arm. Scientists have defined the high-level goals for what the mission has to do—acquire core samples and process them for return, carry science instruments on the arm to help determine what rocks to sample, and so on. We, as engineers, define the next level of requirements that support those goals.

When you’re building a robotic arm for another planet, you want to design something that is robust to the environment as well as robust from fault-protection standpoint. On Mars, we’re talking about an environment where the temperature can vary 100 degrees Celsius over the course of the day, so it’s very challenging thermally. With force sensing for instance, that’s a major problem. Force sensors aren’t typically designed to operate or even survive in temperature ranges that we’re talking about. So a lot of effort has to go into force sensor design and testing.

And then there’s a do-no-harm aspect—you’re sending this piece of hardware 200 million miles away, and you can’t get it back, so you want to make sure your hardware and software are robust and cannot do any harm to the system. It’s definitely a change in mindset from a terrestrial robot, where if you make a mistake, you can repair it.

“Once the rover arrives on Mars and you receive pictures back from it, there’s no greater feeling . . . I have to pinch myself sometimes with the job I do.”
—Matt Robinson, NASA JPL

How do you decide how much redundancy is enough?

That’s always a big question. It comes down to a couple of things, typically: mass and volume. You have a certain amount of mass that’s allocated to the robotic arm and we have a volume that it has to fit within, so those are often the drivers of the amount of redundancy that you can fit. We also have a lot of experience with sending arms to other planets, and at the beginning of projects, we establish a number of requirements that the design has to meet, and that’s where the redundancy is captured.

How much is the design of the arm driven by this need for redundancy, as opposed to trying to pack in all of the instrumentation that you want to have on there to do as much science as possible?

The requirements were driven by a couple of things. We knew roughly how big the instruments on the end of the arm were going to be, so the arm design is partially driven by that, because as the instruments get bigger and heavier, the arm has to get bigger and stronger. We have our coring drill at the end of the arm, and coring requires a certain level of force, so the arm has to be strong enough to do that. Those all became requirements that drove the design of the arm. On top of that, there was also that this arm also has to operate within the Martian environment, so you have things like the temperature changes and thermal expansion—you have to design for that as well. It’s a combination of both, really.

You were a test engineer for the arm used on the MSL rover. What did you learn from Spirit and Opportunity that informed the design of the arm on Curiosity?

Spirit and Opportunity did not have any force-sensing on the robotic arm. We had contact sensors that were good enough. Spirit and Opportunity’s arms were used to place instruments, that’s all it had to do, primarily. When you’re talking about actually acquiring samples, it’s not a matter of just placing the tool—you also have to apply forces to the environment. And once you start doing that, you really need a force sensor to protect you, and also to determine how much load to apply. So that was a big theme, a big difference between MSL and Spirit and Opportunity.

The size grew a lot too. If you look at Spirit and Opportunity, they’re the size of a riding lawnmower. Curiosity and the Mars 2020 rovers are the size of a small car. The Spirit and Opportunity arm was under a meter long, and the 2020 arm is twice that, and it has to apply forces that are much higher than the Spirit and Opportunity arm. From Curiosity to 2020, the payload of the arm grew by 50 percent, but the mass of the arm did not grow a whole lot, because our mass budget was kind of tight. We had to design an arm that was stronger, that had more capability, without adding more mass. That was a big challenge. We were fairly efficient on Curiosity, but on 2020, we sharpened the pencil even more.

Photo: NASA/JPL-Caltech

Three generations of Mars rovers developed at NASA’s Jet Propulsion Laboratory. Front and center: Sojourner rover, which landed on Mars in 1997 as part of the Mars Pathfinder Project. Left: Mars Exploration Rover Project rover (Spirit and Opportunity), which landed on Mars in 2004. Right: Mars Science Laboratory rover (Curiosity), which landed on Mars in August 2012.

MSL used its arm to drill into rocks like Mars 2020 will—how has the experience of operating MSL on Mars changed your thinking on how to make that work?

On MSL, the force sensor was used primarily for fault protection, just to protect the arm from being overloaded. [When drilling] we used a stiffness model of the arm to apply the force. The force sensor was only used in case you overloaded, and that’s very different from doing active force control, where you’re actually using the force sensor in a control loop.

On Mars 2020, we’re taking it to the next step, using the force sensor to actually actively control the level of force, both for pushing on the ground and for doing bit exchange. That’s a key point because fault protection to prevent damage usually has larger error bars. When you’re trying to actually push on the environment to apply force, and you’re doing active force control, the force sensor has to be significantly more accurate.

So a big thing that we learned on MSL—it was the first time we’d actually flown a force sensor, and we learned a lot about how to design and test force sensors to be used on the surface of Mars.

How do you effectively test the Mars 2020 arm on Earth?

That’s a good question. The arm was designed to operate on either Earth or Mars. It’s strong enough to do both. We also have a stiffness model of the arm which includes allows us to compensate for differences in gravity. For testing, we make two copies of the robotic arm. We have our copy that we’re going to fly to Mars, which is what we call our flight model, and we have our engineering model. They’re effectively duplicates of each other. The engineering arm stays on earth, so even once we’ve sent the flight model to Mars, we can continue to test. And if something were to happen, if say a drill bit got stuck in the ground on Mars, we could try to replicate those conditions on Earth with our engineering model arm, and use that to test out different scenarios to overcome the problem.

How much autonomy will the arm have?

We have different models of autonomy. We have pretty high levels flight software and, for instance, we have a command that just says “dock,” that moves the arm does all the force control to the dock the arm with the carousel. For surface interaction, we have stereo cameras on the rover, and those cameras allow us to generate 3D terrain models. Using those 3D terrain models, scientists can select a target on that surface, and then we can position the arm on the target.

Scientists like to select the particular sample targets, because they have very specific types of rocks they’re looking for to sample from. On 2020, we’re providing the ability for the next level of autonomy for the rover to drive up to an area and at least do the initial surveying of that area, so the scientists can select the specific target. So the way that that would happen is, if there’s an area off in the distance that the scientists find potentially interesting, the rover will autonomously drive up to it, and deploy the arm and take all the pictures so that we can generate those 3D terrain models and then the next day the scientists can pick the specific target they want. It’s really cool.

JPL is famous for making robots that operate for far longer than NASA necessarily plans for. What’s it like designing hardware and software for a system that will (hopefully) become part of that legacy?

The way that I look at it is, when you’re building an arm that’s going to go to another planet, all the things that could go wrong… You have to build something that’s robust and that can survive all that. It’s not that we’re trying to overdesign arms so that they’ll end up lasting much, much longer, it’s that, given all the things that you can encounter within a fairly unknown environment, and the level of robustness of the design you have to apply, it just so happens we end up with designs that end up lasting a lot longer than they do. Which is great, but we’re not held to that, although we’re very excited when we see them last that long. Without any calibration, without any maintenance, exactly, it’s amazing. They show their wear over time, but they still operate, it’s super exciting, it’s very inspirational to see.

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