The Autonomous robotics future is around the corner

A world where robots can learn, act, and help humans autonomously has been years in the making.

Intuitive Surgical's robots helped perform 1.6 million surgeries last year, often procedures that would have been impossible for a surgeon alone to perform safely. That's a staggering number until you consider that robotics accounts for less than 0.5% of surgeries performed globally. Robotics is an exciting field that holds the potential to unlock substantial value for society, but it's still in its infancy.

Today, vertical markets like manufacturing, logistics, and medicine deploy robots to sharpen and hasten their workflows. However, they require human control or programming to follow pre-defined rules to operate. Think of factory pick-and-place robots or?Intuitive's DaVinci?doctor-controlled surgical robot. These robots excel at replacing repetitive human tasks, improving output while saving time and costs.?

In the last several years, we've seen the very early adoption of autonomous robots––robots that can perceive their surroundings and act without human input. Autonomous robotics is still a niche field, but we believe that its emergence will expand the entire robotics market in the coming years as it enables higher-value use cases.

In the wake of artificial intelligence's (AI) watershed in 2023, we believe autonomous robotics will soon have its moment, too.?Developers are applying AI technology, like multi-modal and large language models (LLMs), to solving challenging robotics problems, such as?perception, path planning, and motion control.?In this deep dive, we explain why now is the time to start paying attention to autonomous robotics, including recent market developments and growth opportunities.

Why is autonomous robotics relevant now??

Historically, robotics development required significant investments in time and capital to build prototypes. However, recent technological advancements, such as generative artificial intelligence (AI) and neural networks, have accelerated critical phases in the development timeline. Today, robotics has?one of the highest NASA Technological Readiness Levels (TRL)?across deep tech—near-final products are passing tests and approaching commercialization. (Think Cruise’s driverless car service in San Francisco, which became publicly available in 2022.) Now, many are asking the question, “Can autonomous robotics companies become great businesses?”?

Unlike software, it takes a lot of sophisticated inputs to train autonomous robots—more than code alone. Autonomous robotics learn to operate primarily through cameras and computer vision, deep learning, and generative AI.?

Building blocks of autonomous robotics?

1. Cameras and computer vision

Autonomous robots rely on cameras and computer vision technology to perceive their environment. In the future, autonomous robots will use a range of sensors, including Lidar, Radar, Sonar, and other electromagnetic spectrum wavelengths, to perceive the world in a way that is impossible for humans. However, most of?today’s?sensors, other than cameras, are cost-prohibitive for most applications. High-quality cameras, however, have become inexpensive thanks to 20 years of smartphone usage. Smartphone adoption and the associated mass production of cameras have driven substantial improvements in the performance per dollar of cameras in a manner that has not occurred with other sensors. Cameras typically also use passive sensor technology, which is less expensive to manufacture than active sensors such as LiDAR or RADAR. Active sensors usually bounce a wavelength of light off a target and measure the time the beam returns to the sensor.?This?often requires mechanical components, such as the rotating LiDAR sensor seen atop?Google’s?autonomous vehicles, which are more expensive to manufacture at scale than solid-state devices.

Equipped with cameras to help them see, robots need an extra push to help them process what?they’re?seeing. Computer vision technology allows robots to segment objects in one plane and track them as they move across different planes. In other words, it helps them recognize what they see over time and understand the world as humans do.

2. Deep learning and generative AI

To gain autonomy, robots need to be able to learn over time and eventually gain the ability to make decisions on their own. Deep learning, enabled by neural networks, allows robots to make sense of what?they’re?seeing and learn from the commands?they’re?given. Furthermore, recent innovations such as Google?DeepMind’s Robotic Transformer 2?(RT-2) now enable a vision-language-action paradigm whereby robots can ingest camera images, interpret the objects in a scene, and directly predict actions for the robot to perform. Each task requires understanding visual-semantic concepts and the ability to perform robotic control to operate on these concepts, such as?“chop the celery”?or?“clean up the mess.”?This?can potentially reduce the friction between the human-machine interface by allowing humans to direct autonomous robots using natural language rather than esoteric robot programming languages.?

With technological maturity in cameras, computer vision, and deep learning, we get an autonomous robot that can perceive, understand, and learn from its environment. Generative AI removes the friction for human-robot interactions, making communication as easy as speaking to a colleague or friend.

Progress in several peripheral areas has also accelerated innovation where autonomous robotics is concerned:?

• Actuators: Historically one of the weak links for robot design, actuators must be safe, durable, power?and cost efficient?while also generating high levels of torque output and density. The dexterous hardware acts like a human joint, allowing robots to move fluidly.?This?is one of the weak links for robot design because actuators must be safe, durable, power, and cost-efficient while also generating high torque output and density levels. Companies such as ANYbotics are working on some exciting innovations in this area.
• Edge AI compute: Advances in edge computing mean that robots?will be able to?process more powerful computations at the source, delivering quicker and more secure results compared to cloud-based robotic systems where data is sent elsewhere and analyzed.?This?enables a swath of real-time and high-security use cases that?weren’t?previously possible.
• 5G connectivity: Fleets of robots can connect to and learn from one another using 5G, even in areas where WiFi signals are weak. Fleet learning enables learning at scale to unlock an exponential increase in robotic capabilities. Advances in eSIM/iSIM standards and chip availability mean 5G cellular connectivity will become a viable option for many use cases where power usage had previously made it impractical.

Our prediction: autonomous robotics is on its way to help humanity

Regarding autonomous robotics, two ways of autonomy emerge?autonomous?locomotion and autonomous manipulation.?

Autonomous locomotion enables a robot to go from point A to point B independently (think of the Cruise example from earlier). Conversely, autonomous manipulation is where we see the potential for robots that not only impact?productivity,?but protect — and in some cases enhance — human life.

This kind of autonomy enables robots to do human-like, dexterous tasks?on their own, such as pushing things, opening doors, or taking samples.

Having robots perform tasks in high-risk environments, such as oil rigs and nuclear plants, would remove humans from inherently dangerous work environments and prevent several tragic casualties. Companies like Figure, 1X Robotics, and Tesla are already building and testing humanoid robots that can perform mundane and unsafe tasks.?

As companies seek to increase?robots’?autonomy and rely less on remote operation, product developers?will need to?train models on egocentric datasets—visual data from the first-person perspective. New AR/VR products like the Apple Vision Pro offer the potential to accelerate the creation of this training data.

We predict that autonomous and remote manipulation will change several industries, including:?

Medical robotics and automation

Medical robots assist surgeons with non-invasive surgeries, improving surgical processes, ergonomics, and patient outcomes.?

In the future, artificial intelligence (AI) and machine learning (ML) will improve surgical performance and patient outcomes. One day?we?can expect these robots to perform surgeries independently, using deep learning to execute procedures well.

Warehouse and fulfillment robotics and automation

E-commerce fulfillment situations, especially in warehouses, accelerate fulfillment with?the use of roboticsWith?the addition of 3-D vision and 5G enablement, robotics will be able to?take more?more complex tasks within decision-heavy scenarios.??

Construction, cleaning, and inspection

Robots?are leveraged?to inspect work sites (using aerial drones), automate repetitive processes, aid in welding, injection, and finishing, and help clean work sites (Roomba and ECOVACS come to mind).?

As robots get smarter,?they’ll?be deployed in hazardous industrial environments where humans?can’t?safely go and can even guard them with security automation.?They’ll?also contribute to efficiency improvements with tasks like painting, coating, and inspecting machinery.

Human companionship

This one might feel?a bit?more sci-fi than the others, but?it’s?also one of the most exciting future use cases to imagine. As robots gain intelligence and dexterity, they could be available for elderly and disabled people who need help living independently. Having a robot aid in meal preparation, cleaning, personal hygiene—and even friendship—would make a huge difference for those who are struggling.?

Military drones

Uncrewed aerial vehicles (AEVs) can give militaries a competitive advantage in warfare. Companies like?Anduril?are building autonomous drones for military use and autonomous vehicles that can intercept and destroy other drones.?

Hurdles to overcome

Of course, just like any emerging field, the development of robotics has seen its fair share of roadblocks and challenges preventing?wider?commercialization.?We’re?actively looking for companies that are well-versed in the following challenges and looking for innovative ways to overcome them.??

• Hardware-related execution challenges: Robotics technology needs hardware, and hardware is at the mercy of?a long?supply chain. Coordinating these (quite literally) moving parts increases complexity once production?is outsourced. Executing this well is extremely important, and?it’s?also tricky to pull off.
• Capital intensity: Robotics companies need inventory. This results in inventory build-up and RaaS contracts where the company has to hold the robot as an asset on?their?balance sheet. In a world of higher interest rates, financing working capital becomes more expensive.
• Revenue quality: Most robotics companies start?off?by selling hardware for one-time revenue, making it?difficult?to find opportunities for recurring revenue. These companies?haven’t?found a hardware and software combination to generate better revenue. Furthermore, businesses?that have?a mix of recurring and one-time revenue are often more difficult for the investor community to assess since traditional SaaS KPIs may not be applicable.
• Employment: Robotic automation disrupts global employment. On average, the arrival of one industrial robot in a local labor market coincides with an employment drop of 5.6 workers.?This?will apply pressure to policymakers, so?we’re?asking companies to think of how regulation might impact their vision from day one.

Our guiding principles on how we will invest

We’re?looking to back?strong technical?teams with deep robotics engineering and supply chain expertise?in building autonomous robots that?enable previously impossible tasks.?This?is our top criteria. Beyond this,?we’re?interested in startups that aspire to?build?businesses that can achieve the following:

• Disrupt Large?markets:?Targeting large Total Addressable Markets (TAMs) when calculated on a bottoms-up basis.?
• Enable complex use cases:?We’re?not interested in labor arbitrage (low level) use cases;?there’s?already plenty of activity in these markets. Instead,?we’re?looking for use cases that, at the very least, protect human life. Ultimately, we want to move?in the direction of?enabling things that humans previously?couldn’t?physically or technically achieve (like our oil rig example above).?
• Connected, cloud-based fleets:?Remote telemetry for fleet learning is a particular feature?we’re?on the lookout for.?Equipped with remote telemetry, robots can transmit data to other nearby robots on the fly, who can then take that data and learn from it.?We’re?also looking for companies that are actively thinking about autonomous manipulation.
• Recurring revenue and high average revenue per account (ARPAs):?A portion of revenue must be recurring, and?average?selling price (ASP) must be six figures, with tons of room available to increase actual cash value (ACV) and ARPA. As a directional example, think more Intuitive Surgical and less Roomba. Even if penetration is low, these metrics?would?signal that the?room?to penetrate is much higher.?
• Traction forward is a bonus:?We’re?looking for companies with robots in active use in production environments for at least?6?months and avoiding firms where the sales have solely been to innovation groups.?

The road ahead with autonomous robotics

The technology behind autonomous robotics is closer than ever to widespread deployment.?From medical and warehouse use cases to construction and companionship, we expect to see autonomous robotics touch?a?diverse?set of?industries.

Also on the horizon is teleoperation—robotics manufacturers and customers have the opportunity?to remotely operate?robots,?and?in?some?cases?can assign the work to people in other parts of the world. ANYbotics, for instance, has been experimenting with?teleoperation since 2019, when it announced one of its products could perform industrial inspection tasks, like checking energy plants for rust and leakages, via teleoperation. When Elon Musk shared a video of?Tesla’s?humanoid robot Optimus folding a shirt, he?explained?it was remotely operated. Phantom Auto, too, built a platform that enables factory workers to operate forklifts remotely. Teleoperation represents a meaningful intermediate step between?today’s?human-controlled, in-person?robots?and fully autonomous robots.

Even with all the data and use cases we currently have, we?can’t?make a definitive prediction about autonomous?robotics's?future. But with the right investments and resourcing,?it’s?not hard to imagine how further advancements will make a staggering number of?“what if?”?scenarios a reality.?

If you are building in the autonomous robotics space, we’d love to hear from you,

Feel free to reach us at : [email protected]