Robotics

There’s a new role that is becoming an integral part of many warehouses, distribution centers and factories globally: the robot expert. As labor shortages strain the manufacturing and supply chain sectors, business leaders need to realize the value of the robot expert and how they can help solve these challenges. By upskilling individuals to manage a team of robots, mundane tasks can be left to the machines while experts handle big picture thinking and overall management of the warehouse. But where do decision makers, who often see a need but don’t have technical expertise in automation, start looking? Where are the opportunities and what’s at stake for companies that don’t adapt?To gain insights into these and other questions about this new role and growing opportunity, I reached out to Bryan Siegal, VP, Customer Success, Vecna Robotics, as well as Mahesh Nikam, Shape Excellence System Manager, Shape Corp.GN: How is the rise of automation catching some companies off guard or flat footed and what are some ways that you’ve seen companies arrive at the moment of adoption unprepared for the challenges ahead?Bryan Siegal: We are hearing from most of our customers that business has now boomed to levels they have never seen before and it has pushed demands beyond the capacity of their sites. Many have gone to extended days and shifts. Finding associates to work the added shifts is a major problem to meet all their demand. These companies are caught flat footed by not having the extra capacity needed where they could otherwise have literally turned the switch and let the robots run longer. Instead, they are having to turn away revenue because they simply can’t find the resources to get it done.The other big factor is that adopting robots takes time. Change management must be considered, including updating processes, training staff, effective reporting and management, etc. So, organizations that invest early and learn how to effectively use robots in their operations have a massive advantage over those that don’t. GN: Can you describe what an internal Robot Expert is and various ways the role can help a company?

Bryan Siegal: The internal robot experts are associates who have been trained to interact with and operate the robot fleet at an advanced level. In this capacity, the robot expert is the on-shift expert ensuring the fleet is on mission as well as answering questions from other associates as needed and dealing with any “exceptions” as they arise. Beyond local fleet oversight, the robot expert is the prime point of contact for our Network Operations Center (NOC) team who provide 24×7 proactive remote monitoring to ensure the fleet is running optimally. Consequently, the robot expert is key to ensure the productivity gains enabled by a fleet of robots is returned to the company.GN: When is the right time in a company’s trajectory or growth to create a role like this?Bryan Siegal: When a company’s growth rate, ability to find labor, or cost structure, forces them to realize they cannot keep up with competition, they often decide that autonomous equipment like our self-driving forklifts and tuggers are the solution. The team then creates a project plan for roll-out and continued operations. During that process, they appoint a team of robot experts  for all shifts the fleet will be operating. The Robot Expert plays a key role in assisting with the deployment of the fleet as well as operating the fleet once fully deployed.GN: Mahesh, I’d like to bring your experience at Shape to bear here as well. What sort of existing employees tend to make great Robot Experts and how does SHAPE CORP. support their transition to that very new role? Mahesh Nikam: Currently, Shape is transitioning to automated material handling by developing our current team members specializing in forklift operation and utilizing their proficiency in this area to mold them into Autonomous Mobile Robot experts. We provide team members with an in-depth training on AMR safety and functionality along with hands-on training to help further develop their skill-set in this area. After team members complete their training they then receive an update on their Industrial Vehicle license for AMR. We want to ensure our team is set up for success for all development opportunities we provide at Shape.GN: Bryan, how about from your perspective? What do the best candidates for the role have in common?Bryan Siegal: The best candidates for the Robot Expert role exhibit several things: comfort working with industrial equipment, demonstrated skills working with software, excitement about working with cutting edge technology, and a deep understanding of the day-to-day flow in their working environments. Above all, these are folks who want to see the company grow and succeed. These qualifications are often learned on the job, and candidates are often associates with several years of operational experience. They may also be supervisory level individuals, but all have an open mind and willingness to see new technology help transform their operations. By contrast, they do not have to be degreed engineers as we are not asking the Robot Expert to diagnose and repair robot problems. We  work virtually alongside the expert and through this partnership to diagnose and resolve issues via our 24×7 NOC center. This collaboration is essentially an “on the job training” that propels their career forward as they grow and learn how to manage these types of systems. As this role becomes a mainstay, companies and industries should establish the role as a formal role and  a career choice.GN: What resources, education or professional development-focused, are available for would-be Robot Experts? Bryan Siegal: This is an emerging role tied to the deployment of AMRs. At this early life-cycle stage across the AMR industry, training is limited to one-on-one highly personalized training with customized collateral.That being said, there are a few specialized areas where training would be beneficial. Robots use sensors to see the world. This includes cameras, Lidars (generally a rotating laser range finder), Ultra-sonic range finders, time of flight cameras and others. Understanding how those sensors work, and common failure modes can be extremely helpful in ensuring top performance of the robots. Another area of training is wireless networking since almost all robots depend on the wireless network for operation. Vecna Robotics’ AMRs are connected to the customer’s WiFi or cellular network. This  is how we maintain communication with the AMR. Improving the robot experts’ understanding of the network needs and operational environment will make that person a valuable asset not only to us, but to the operation overall.  The third area of specialized training that can be helpful is around robot safety.  Safety requirements for these systems are stringent, and if the staff doesn’t understand how the safety systems work, it can be frustrating as they ask, “why isn’t the robot moving?” Unlike manually-operated equipment, robots are mandated to have certain stand-off distances from other objects. Information on all of these key areas can be found on Vecna Robotics’ and MassRobotics’ websites. GN: Mahesh, as SHAPE CORP. grows and the company’s automation needs mature, and Bryan, as the same happens to Vecna and the companies it supports, how do you both expect the role of Robot Expert to change and evolve? Mahesh Nikam: Our vision at Shape is to have our AMR Fleet servicing all production lines and keep manually operated forklifts only in areas we specify. With an expansion of AMRs we are envisioning to have a central area where AMR Experts manage the fleet with an automated order system. As we grow, this role will evolve even more by optimizing AMR routes, co-coordinating and supporting the implementation of new AMRs as well as training and onboarding new teams to assist with the management of this pivotal asset to Shape’s growth.Bryan Siegal: Much like the training and expertise of a car mechanic has evolved along with the evolution of automobile technology, I expect the role of the Robot Expert will change as AMRs become smarter through newer sensors, faster computer processing power and more sophisticated AI algorithms. The combination of these improvements will result in AMRs being capable of performing more sophisticated jobs, working faster in teams (both human and robot teams) and allowing for greater operational throughput. Part of the career path here will be growing from operating the robots, to learning how to effectively deploy new robots as the tools to do that become more mature and accessible to workers without advanced engineering degrees. The Robot Expert will also become part of the operational decision-making level across a site, because their knowledge of how to achieve the best outcomes using the robots will be valuable as site changes and updates are considered. More

Here’s a head scratcher: You’ve got a space ship and you’ve just left earth’s orbit. There’s a space station around here somewhere, but how do you navigate to it?

Using a surprisingly cumbersome set of tools and onboard sensors, it turns out. In an age when you can sail across an ocean or climb a remote peak and instantly determine your precise location on a small device equipped with a GPS receiver, it’s easy to think humans have navigation nailed. But that network only works on our little planet. As space travel becomes a reality for a growing subset of people and commercial enterprises, navigation remains a big hurdle.”Unlike Earth, the Moon isn’t equipped with GPS so lunar spacecraft and orbital assets are essentially operating in the dark,” said Matthew Kuhns, vice president of research and development at Masten Space Systems, which has been building and flying reusable rockets for nearly two decades. “As a result, each spacecraft is required to carry heavy navigation hardware and sensors on-board to estimate positioning and detect potential hazards. By establishing a shared navigation network on the Moon, we can lower spacecraft costs by millions of dollars, increase payload capacity, and improve landing accuracy near the most resource-rich sites on the Moon.”That’s precisely what Masten is setting out to do thanks to a Phase II SBIR contract through the Air Force Research Laboratory’s AFWERX program to develop and demonstrate a lunar positioning and navigation network prototype. If that sounds similar to GPS, it’s because the system is being modeled to function similarly. Under a similar contract, Masten has already completed the concept design for the network prototype that offloads position, navigation, and timing (PNT) beacons from a spacecraft into a dedicated sensor array on the Moon. The next phase of the project, set to be complete in 2023, focuses on designing the PNT beacons. The devices must be extremely durable to survive lunar conditions, and for help in that arena it’s turning to engineering and defense firm Leidos.”As one of the first commercial companies sending a lunar lander to the Moon, we’re in a unique position to develop and deploy a shared navigation system that can support other government and commercial missions and enable a thriving lunar ecosystem,” said Masten CEO Sean Mahoney. “We are literally blazing the trail with this effort, creating the pathway for regular, ongoing, and reliable access to the Moon.”The idea is to deploy shock-proof beacon enclosures that will penetrate the lunar surface and create an autonomous surface-based network that’s similar to a mesh network. The network, if effective, will enable consistent wireless connectivity to lunar spacecraft, objects, and orbital assets. 

Masten’s rocket-powered lander, Xodiac, will be used to test the PNT beacons and to demonstrate payload integration and beacon operations in a terrestrial environment. More

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Here’s an interesting question: Could an AI do a better job coaching a professional sports franchise? We’re certainly not there yet, but given how readily professional teams adopt technology to give their players an edge, that mind-bender might not be completely unthinkable in the years ahead.The concept recently got a test run thanks to, of all things, a sports betting website called SportsBettingDime, which enlisted OpenAI’s latest text generator, GPT-3, to see if AI could emulate a head coach. The study (full results here) prompted GPT-3 to generate motivational speeches, handle in-game scenarios, and promote team building, which is among the important functions of a head coach in many sports. The site then asked NBA and NFL superfans how GPT-3 performed.Corny as those movie moments may be, motivational speeches really are a key function of many coaches’ jobs, rallying players with the right dose of reality or inspiration at the right moment. The study used GPT-3 to generate three separate speech snippets and then mixed in two real speeches from coaches. NFL and NBA fans were then asked for their unbiased opinions.”As opposed to tactics and gameplan, speeches are one of the more human responsibilities of a head coach that data can’t answer. Surprisingly, AI seemed to hold its ground in providing motivation and emotional support, according to superfans,” according to the study.In fact, the two of the AI speeches ranked highest in this admittedly loosely controlled test, receiving motivational ratings of 6.82 and 6.47, respectively. However, it must be noted that the third AI speech came in dead last, suggesting marked variability in outcome. Interestingly, the motivational value didn’t necessarily equate to how human the speeches sounded, at least not to the fans who participated in the study. Both of the authentic human speeches were ranked as having likely been given by a real coach (77.8% and 66.3%, respectively), while AI speech realness ranged from 66.4% real-sounding to just 51%.The study also evaluated the AI’s decision-making in game scenarios against the plays the superfans would have called. Scenarios were evaluated first in an NFL situation:

Scenario AOn a 4th and 1 with limited time left, AI would call a run play for the first down, specifically calling the running back’s number. Many NFL superfans would disagree: 31.9% would run a quick pass play, although 22.2% agreed with AI on an RB run play. AI’s emphasis on this last drive for the win was to get in range for an FG to tie instead of taking the risk for a TD to win the game. With 50.8% of them agreeing with AI to get in range for an FG and 49.2% disagreeing, NFL superfans were split.Scenario B  Following a touchdown with no time left and being down 1 point, AI would go for a 2-point conversion to win the game as opposed to a less risky extra point to tie. Again, NFL superfans were pretty split, with 48.2% agreeing with AI and 58.8% disagreeing.The likewise evaluated play calling in high-pressure NBA scenarios:Scenario ADown 2 points with 10 seconds left on offense, AI would run a set play, specifically looking for a 2-point jump shot. Most NBA superfans would deviate from that strategy; 28.2% would run a set play for a 3-pointer to win the game, and 19.5% would isolate their star player. Still, 22.2% agreed with AI on a set play for a 2-pointer. AI believed the best offensive option in this scenario was to go for 2 points, specifically a jump shot. NBA superfans were somewhat split, with 55.5% of them agreeing with AI to go for a tie (2-pointer) and 45.5% disagreeing.Scenario BIn this defensive scenario, AI would emphasize denying the ball from the other team’s best player and defending without fouling. As their top two emphases lined up with AI, NBA superfans agreed with AI (46.7% agreed with denying the ball from the other team’s best player, and 33.6% agreed with not fouling).The study results, which, again, is hardly the kind of scientific evaluation needed even to approach answering the question, present some interesting anecdotal takeaways. As a motivational speaker, GPT-3 was surprisingly competent. However, when it came to designing specific play calls, AI seems not to have made the best decision in the eyes of those identified as superfans. However, AI was able to be decisive in scenarios where superfans were split, which points to one possible advantage to AI over humans: computers aren’t emotional. They may be more able to act decisively (and quickly) in crucial moments.Will AI take over from your team’s head coach? Probably no time soon. Should an AI take over when the technology reaches or exceeds a threshold of parity? Depending on how you did last season (or are doing this season), your answer may vary. More

We’re a couple of decades into the 21st century, cars are literally starting to fly, a vacation to space is just around the corner … and yet somehow, computers still sound like parodies of confused robots whenever asked to convert text-to-speech (TTS). Come on, devs, there has to be a better solution. A firm called WellSaid Labs believes it has one, and it’s getting a boost thanks to an oversubscribed Series A.”Plain and simple, WellSaid is the future of content creation for voice. This is why thousands of customers love using the product daily with off-the-charts bottom-up adoption. Matt and Michael have assembled a world-class team, and we couldn’t be more thrilled to be a part of the WellSaid journey,” says Cameron Borumand, General Partner at FUSE, which led the round.I’ll just cut to the chase and tell you you can listen to samples of the voices here.The problem of making a digitized voice sound human when converting text to speech is deceptively complex, one of the grand challenges in the field of AI and a subject of considerable research in fields like computer science, human-machine-interface, and robotics. In June 2020, according to a statement, WellSaid Labs’ text-to-speech became the first to achieve human parity for naturalness on short audio clips across multiple voices.”We’ve added AI Voice to the toolkit of thousands of content creators and their teams,” says Matt Hocking, CEO of WellSaid Labs. “Our human-parity AI voice can be produced faster than real-time and updated on-demand. Opening up new and exciting opportunities to “add voice” was never before perceived possible. AI voice easily ensures every production can be created and updated efficiently at scale.” The human parity milestone has significant implications for how audio content is created, which has made investors keen to jump on board. Use cases include streaming services, radio, programmatic advertising, digital marketing, and corporate training content. WellSaid Labs has a Voice Avatar library that provides access to multiple read styles and tones. In addition, brands can create their own AI Voice Avatars to capture the voice’s likeliness, style, and uniqueness needed to tell their stories. 

“Content creators or product experience designers were previously faced with difficult tradeoffs between quality and scalability when using TTS tools or human voiceover. WellSaid’s incredible voices, accessible through a studio application or a scalable API, remove the need to choose whether you want natural, lifelike speech or infinitely scalable and easily editable voice content. WellSaid provides both and delivers it however your team would like to consume it,” says James Newell of Voyager Capital. “Creative teams have found it to be extremely useful when they need to produce multiple pieces of high-quality content in a consistent voice in hours instead of weeks.” More

Fetch
A pioneer in the exploding market for warehouse logistics automation is being acquired in a major deal. Fetch Robotics will join Zebra Technologies in a deal reportedly worth $290m. Zebra was previously an investor in Fetch and already owned 5% of the robotics firm.The announcement comes at a time of rapid growth in the automation market, particularly in the logistics sector. The surge of online shopping during the pandemicand the increasing demand for rapid shipping have caused a scramble third-party logistics companies to rethink their operations with efficiency in mind. Amazon, which acquired logistics automation firm Kiva back in 2012, is largely responsible for starting the rapid delivery paradigm.Founded in 2014 by Melonee Wise, a robotics pioneer and alumnus of famed robotics research lab Willow Garage, Fetch has helped pioneer a new category of industrial automation that can be flexibly scaled to meet demand. In addition to its autonomous mobile robots, which include a cart that can autonomously navigate a warehouse and a mobile pick-and-place robot, the company touts its cloud-based robotics solution, which integrates a full automation stack into logistics operations of all sizes, whether a company needs just a few robots or dozens.The business case emphasizes speed, which automation provides, and labor shortages, which have been a top of list concern for managers in a tight labor market that’s now years old. Companies like Fetch and its competitors, which include Locus Robotics and Geek+, have stepped into the fray to fill that need with flexible automation offerings.”The competitive pressures for excellence in logistics have never been greater,” Wise told me in 2019.Fetch currently boasts the largest portfolio of autonomous mobile robots (AMRs) in the industry and offers integration with warehouse and manufacturing systems without the need for changes to facilities or infrastructure.

“The acquisition of Fetch Robotics will accelerate our Enterprise Asset Intelligence vision and growth in intelligent industrial automation by embracing new modes of empowering workflows and helping our customers operate more efficiently in increasingly automated, data-powered environments,” says  Anders Gustafsson, Chief Executive Officer of Zebra Technologies. “This move will also extend our ongoing commitment to optimizing the supply chain from the point of production to the point of consumption. We are excited to welcome the Fetch team to the Zebra family.” Zebra is leaning hard into the logistics and fulfillment space, with a portfolio that focuses on robotics automation that combines workflow solutions for human workers, including Zebra offerings such as FulfillmentEdge and SmartSight, with Fetch Robotics’ solutions.  More

Water sampling and analysis methods today are logistically complex, labor-intensive, time-consuming, and costly. Could drones, which are relatively cheap provide part of the solution? After two years of research and development, a company called Reign Maker believes the answer is yes as it roles out the world’s first drone-based water sampling and data collection system, designed to increase sampling rates and accuracy while reducing reliance on field personnel and equipment, such as boats and boots.The solution is called Nixie, and the company claims it can increase sample rates by 75% while reducing costs by 90%. 

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“The New York City Department of Environmental Protection alone collects 14,000 water quality samples a year, collecting 30 samples a day using boats, captains, and a crew of three at an average cost of $100 per sample,” says founder and CEO Jessica Chosid. “With Nixie, a crew of two can collect 120 samples in the same seven-hour shift, at a cost as low as $10 per dip.”The drone collects samples by lowering EPA certified bottles exactly two feet under the water’s surface in currents up to 5 knots. The approach is important because it eliminates a common problem with manual sampling, which is that sediment and debris are often stirred up by technicians, reducing sampling accuracy. Nixie registers the GPS location and timestamps every sample it collects, allowing water managers to closely track changes in water chemistry by time and location.Applications include public-private utilities, oil & gas, environmental monitoring, mining, agriculture, and disaster and spill mitigation.The system currently supports DJI M600 and M300 RTK enterprise drone platforms, which it says have proven safety, reliability, versatility, and ease of use. DJI is currently on the U.S. Entity list.

Drones of various kinds are being used more frequently for environmental and infrastructure monitoring. Singapore, for example, recently sent out drones to watch over its reservoirs and monitor water quality. Ocean-going sailing drones have also been deployed in aid of environmental monitoring. Nixie commercializes the approach with a new technology suite designed to be used in a number of sectors.”With Nixie, we are committed to changing how water is analyzed worldwide, one sample at a time,” said Jessica Chosid, Founder and CEO of Reign Maker. “Our mission is to remotely collect, digitize, and transform commercial,  industrial, and agricultural water management across the supply chain.” More

Those painted road markings on highways don’t seem like much, but study after study show that they save many lives. Keeping track of faded lane dividers, potholes, and other hazards on America’s 4 million miles of roads is a tall task but the data already exists — being recorded every day by dash cams.That’s the premise behind a new collaboration between Nexar, whose popular dash cams are in hundreds of thousands of cars covering millions of miles of roads a day, and Blyncsy, a movement and data intelligence company headquartered in Salt Lake City, Utah. Blyncsy will ingest billions of images collected by Nexar’s popular dash cams to support pilot programs for the New Mexico Department of Transportation, CalTrans, Utah, and other departments nationwide.”We know that machine learning is only as strong as the data it depends on,” says Mark Pittman, CEO and founder of Blyncsy. “With this partnership, we’re giving government agencies a magnifying glass for their infrastructure, plus the power of continuous pattern analysis and predictive analytics. We’re excited to see how this combination can impact public servants, communities, and people everywhere.” According to federal data, half of fatalities on America’s roadways result when motorists leave their travel lanes, making this a problem of enormous consequence. Asphalt pavement markings are a huge factor in reducing lane departure incidents, but DOTs have trouble determining where and when markings need to be upgraded with any reliability. With over four million miles of highway in the U.S., pot holes are similarly difficult for DOTs to reliably find and fix in a timely manner.Through the power of AI, billions of images collected by the dash cams may help. The images are mapped, contextualized, analyzed, and can be presented to state DOTs on a dashboard showing them in real time where repairs are needed. 

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“We are proud to partner with Blyncsy using our combined AI smart technology to improve our roads,” says Eran Shir, CEO and co-founder of Nexar. “With many cities investing in expensive lidar technologies to monitor their streets and roads, or human surveyors, the crowdsourced vision data from Nexar ‘sees’ the world at eye-level just like we do and provides superior insights at a fraction of the cost. Pavement monitoring is just one example of Nexar’s value while other cities and businesses are using the data to monitor and understand curb use, real estate trends, pedestrian traffic, construction, and more. Nexar creates a platform that other companies can run their AI on and in some cases applies its own AI, such as work zone detections in the Las Vegas Valley.” More

A new collaboration between space exploration technology companies has resulted in a novel approach to extracting water from the moon, a key step for possible human colonization. Masten Space Systems teamed up with Honeybee Robotics and Lunar Outpost to design a Rocket Mining System that can disrupt lunar soil with a series of rocket plumes.The rockets fluidize the ice regolith found in certain areas of moon, including the satellite’s south pole, with direct convective heating. The system can recover more than 420,000 kg of lunar water per year utilizing a rocket engine under a pressurized dome to enable deep cratering more than 2 meters below the lunar surface. Ejecta from multiple rocket firings soars into the dome, where it’s funneled through a vacuum-like system that separates ice particles from dust.

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Water extraction is considered a key ingredient in the quickening race to inhabit the moon and eventually other extraterrestrial bodies. Usable as drinking water, rocket fuel, and other vital resources, lunar ice extraction can enable a sustained presence on the moon and can also be used in conjunction with other volatiles found in lunar regolith, such as oxygen and methane, to support energy, construction, and manufacturing.”As one of the first commercial companies sending a lunar lander to the Moon, Masten is in a unique position to deploy this system,” according to a company blog post. “We’ve been testing plume surface interactions with our reusable rockets and engine test stands for more than a decade. The tests we conduct have allowed us to collect cratering data using a frozen lunar regolith simulant at our facilities in Mojave.”Rocket mining, according to Masten, is preferable to mechanical excavation using drills and other equipment due to its cost effectiveness and scalability. Whereas it would be challenging to send enough drilling equipment to the moon to extract usable quantities of water, the rocket mining rig designed through the current collaboration fits inside a small rover.Because it relies on convective heat, this approach also permits mining around obstacles like boulders. Perhaps best yet, it’s largely self-sustaining. Solar energy can be used to electrolyze the stored water into oxygen and hydrogen to continue powering the rocket engine for years. Building on decades of experiments Masten is preparing to build a prototype of the rig for testing.  More