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Realtime Robotics closes $2 million seed round

Posted on by Erin

Investors include SPARX Group Ltd., Scrum Ventures, and Toyota AI Ventures

BOSTON, MA – October 30, 2017— Realtime Robotics, which develops breakthrough technology that unleashes robots and autonomous vehicles from their current limitations, announced today that it has secured $2 million in seed funding to further its growth. Key investors in the seed round include SPARX Group Ltd., Scrum Ventures, and Toyota AI Ventures, a venture capital subsidiary of Toyota Research Institute (TRI).

Founded in March 2016 by Duke University professors Dan Sorin and George Konidaris, Realtime Robotics enables complex robotic motion planning tasks to be accomplished up to 10,000 times faster than previously possible using a proprietary special-purpose processor – allowing robotic systems to instantly react to their environments, and compute how and where to move as their situation is changing. This groundbreaking ability to instantly plan motion in response to rapidly changing conditions overcomes one of the primary challenges preventing robots and autonomous vehicles from achieving their enormous potential.

“We’re currently working with major multinational customers to create highly adaptable robotic systems for application to new classes of industrial tasks, many times larger than the existing robotics market,” said Realtime Robotics CEO Peter Howard. “In addition, we’re excited about the role that Realtime’s technology can play in improving the safety of emerging autonomous driving platforms, even in complex urban driving environments.”

Realtime’s lightning-fast processor enables robots with sophisticated arms to be utilized in dynamic environments, dramatically increasing the types of industrial tasks they can perform. Realtime’s processor can also be used by autonomous vehicles to help them operate at normal speeds—like humans, but safer—instead of slowing to a crawl when there is uncertainty regarding other cars, bikes, or pedestrians.

“The technology being developed by Realtime Robotics is game-changing, and we’re proud to be part of this investment through Toyota AI Ventures,” said James Kuffner, TRI’s Chief Technology Officer. “We share Realtime’s commitment to enabling robotic systems to perform complex tasks quicker, safer and more efficiently.”

Realtime Robotics is hiring talented roboticists and software engineers to join its founding team in realizing the broad market applications for this breakthrough technology. The company has a growing list of clients, ample funding, exciting technology, and broad application areas under development. Get in touch for more information or explore career opportunities.


Media Contact
Maggie Weeks
marketing@rtr.ai

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James Kuffner, CTO at Toyota Research Institute, blogs about Realtime Robotics

Posted on by Erin

Welcoming Realtime Robotics to the Toyota AI Ventures portfolio

By James Kuffner, Chief Technology Officer, Toyota Research Institute

Excerpt:

Visions of the future often feature robots. Whether working in factories, attending to humans, or piloting our cars, they compose a large part of our futurescape. While we imagine how robots could vastly improve our lives, a challenge roboticists inevitably come up against is: how do we build robots that can safely move in our complex world? The field of robot motion planning has emerged with the goal of addressing this challenge.

Read full article

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We welcome Jason Barton to our team!

Posted on by Erin

Realtime Robotics on-boards Jason Barton as Chief Commercial Officer

Bringing robotics industry and global go-to-market expertise to robotics start-­up

Boston, MA – Nov 26th, 2018 –Realtime Robotics, Inc. today announced it has hired Jason Barton to serve as the Company’s Chief Commercial Officer, effective October 30th, 2018. Founded by Prof. George Konidaris and Prof. Daniel Sorin, Realtime Robotics has invented a specialized processor for generating safe robotic motion plans in microseconds, enabling robots to function in unstructured, collaborative works-spaces, reacting to a dynamic world in the instant changes are perceived.   The Company is heading toward production and sales of its products, and has brought Mr. Barton in to guide the global commercial strategy and lead revenue growth.

Mr. Barton has 20+ years of sales and marketing leadership experience selling high-tech disruptive products and solutions into global markets.  At Rethink Robotics, he helped create the collaborative robot category building a sales and support network that served manufacturing plants across the globe.  Prior to this he has served as COO of EnergyHub, a leader in connected home energy management solutions. He also ran sales and marketing at Segway, and for Palm’s US Enterprise business.  Jason earned a BA Honors Degree from the University of Wales in the UK.

I’m delighted to be joining such a talented and innovative team”  said Barton. “Realtime’s technology is a game changer for robot applications and autonomous vehicles.  Safe, quick, collision-free motion planning is instrumental in enabling the adoption of robotic solutions in the unstructured and dynamic environments that make up the bulk of human activity.”

“We are all thrilled to have Jason join us at this key juncture, as we finish out our successful Beta phase and move toward a series of progressive commercial releases over the next 18 months.  Jason’s depth of experience both in industrial robotics and in early stage transitions to commercialization is a perfect fit, and already generating enormous value”, said  Peter Howard, Realtime Robotics’ CEO.

About Realtime Robotics

Realtime Robotics was founded in March 2016 by Duke University professors Dan Sorin (Computer Architecture), George Konidaris (Robotics and Motion Planning), and a few of their top researchers, based on their groundbreaking DARPA-funded research. The Company is currently working with major multinational customers to create highly adaptable robotic systems for application to the vast majority of industrial tasks which are in dynamic environments, as well as to enable autonomous driving platforms to achieve superior safety at normal driving speeds, even in the complex urban driving environments that are the key challenge to the technology’s widespread adoption.

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Realtime Robotics in the news: Medium

Posted on by Erin

Self-driving Cars vs Humans — 100x Power Efficiency Gap

By Nitin Vaish

Excerpt:

The development of self-driving cars is moving rapidly, with Waymo launching the self-driving car service on the road without front safety driver earlier this month. Kudos to the team! It’s an awesome outcome of the research that was spurred by Darpa urban challenge almost a decade ago.

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Realtime Robotics Named Finalist in Automate Launch Pad Startup Competition

Posted on by Erin

Enables Robots to Operate Collision-Free in Dynamic, Unstructured Environments

BOSTON (Mar. 26, 2019) – Realtime Robotics, an innovative automation startup incubated at MassRobotics, has been selected from a highly competitive field as a finalist in the Launch Pad Startup Competition to be held at Automate in Chicago.  The company, along with six others, will pitch its technology solution to a panel of judges and vie for a $10,000 prize on Wed., Apr. 10 at 3 pm CT at McCormick Place’s “Win the Future” theater.

Realtime Robotics is changing the way robots interact with the real world of factory and warehouse operations. While demand for increased automation among manufacturers and distributors of all sizes is on the rise, there are significant obstacles to the widespread adoption of both industrial and collaborative robots:

  • the costs associated with ensuring the safety of people in and around the work-cell
  • the inability to navigate seamlessly in dynamic environments
  • the need to slow down performance in order for robots to be safe and accurate

Realtime Robotics’ solution for collision-free motion planning eliminates these challenges. Built on next-generation computer processing and innovative software, its products make it possible for robots to navigate dynamic environments smoothly, quickly and intuitively.

“We’re excited to be a part of this showcase of companies that are driving automation forward,” said Jason Barton, Chief Commercial Officer of Realtime Robotics. “We believe that when robots break free from the constraints which limit their ability to work with people, the real benefits of automation will finally become a reality.”

To learn more about Realtime Robotics, its technology and the business benefits it offers, please visit booth #9649 at the Automate show, and the company’s website.

About Realtime Robotics

Boston-based Realtime Robotics was founded in 2016 by Duke University professors Dan Sorin, George Konidaris and top researchers Sean Murray and Will Floyd-Jones, based on groundbreaking DARPA-funded research in motion planning. The company is working with global customers and partners to transform industrial automation by enabling robots to recognize, respond and decide how and where to move in milliseconds, even in variable environments.


Company contact:
Maggie Weeks
marketing@rtr.ai

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Solving the Autonomous Vehicle Safety Challenges

Posted on by Erin

The future of driving is automated.  The certainty of this future—despite well-publicized delays and technical challenges—derives from the numerous and substantial benefits of autonomous vehicles (AVs).  The potential safety benefits are extraordinary. At least 31% of road deaths happen in DUI crashes, and an additional 10% occur when the driver is either distracted or drowsy; up to 90% of all accidents are caused by driver error. An NHTSA report estimated the total societal harm from vehicle crashes at $836 billion, a number that could be significantly mitigated with autonomous vehicles.  In addition to safety, AVs would provide mobility for the disabled, elderly, and children who cannot drive themselves. And, perhaps most practically, AVs would free most of us up from having to drive ourselves when commuting to and from work.

Given all of the benefits of AVs and the hype about them, why are they not here already?  Yes, there are promotional videos in which AVs glide down the freeway. Yes, pilot programs exist in which a small number of AVs operate in a constrained area and only under optimal conditions (e.g., good lighting, good road conditions).  Yes, many new vehicles come equipped with more autonomy than the simple cruise control of previous decades. And yes, many of us have seen videos of AVs poking along hesitantly in urban environments. Nevertheless, none of us are routinely lounging in an AV that is driving naturally—at normal speeds and without being confounded by four-way stops and pedestrians—through a city.

The potential market is enormous with the latest data predicting that AVs will be the fastest-growing automotive sector with sales crossing more than 11 million units by 2033 with a compound annual growth rate of 76.09 percent to 2033.  Allied Market Research estimates that the AV market will reach $54 billion by the end of 2019 and then will explode to $556 billion by 2026. The anticipated growth is reflected in the flurry of M&A activity in the sector as automakers, suppliers and technology players in the space to continue vertical integration and consolidation.

However, before fully autonomous vehicles can become commonplace in urban environments, there are still safety challenges that need to be overcome.  Solving this issue is the key to making autonomous driving and vehicles a reality. In our next blog, we will dive into autonomous driving and how we’re overcoming the critical technical challenge.

You can also read more about our philosophy in this recent IEEE article.

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Autonomous Driving and the Need For Motion Planning

Posted on by Erin

Our last blog outlined why autonomous vehicles are not a passing fad and are the future of transportation. However to realize their full potential motion planning is an essential component that will address a myriad of safety challenges. Before we dive into motion planning let’s look at autonomous driving in more detail.

There are many aspects to autonomous driving, all of which need to perform well. You can think of autonomous driving as a four-level stack of activities, in the following top-down order: route planning, behavior planning, motion planning, and physical control.

  1. Route Planning determines the sequence of roads to get from location A to B.
  2. Behavior Planning is the process of determining specific, concrete waypoints along the planned route.  These goals can vary based on road conditions, traffic, and road signage, among other factors.
  3. Motion Planning computes a path from the vehicle’s current position to a waypoint specified by the driving task planner.  This path should be collision-free and likely achieve other goals, such as staying within the lane boundaries.
  4. Physical Control is the process of converting desired speeds and orientations into actual steering and acceleration of the vehicle.

All four levels rely on accurate perception and this is where the majority of solutions continue to emerge. However, control of the car ultimately boils down to these four control levels, and of these, motion planning is the current technical bottleneck and is the primary obstacle to the adoption of AVs.

The current state-of-the-art for motion planning leverages high-performance commodity GPUs. Yet even with a “500-watt supercomputer in the trunk,” as one of our customers recently described it to us, they could compute only three plans per second. Even given high-performance GPUs, motion planning is too computationally difficult for commodity processors to achieve the required performance.

realtime-reaction-time-300x300

What is the required motion planning performance?  At an absolute minimum, the motion planner must be able to react—that is, create a new motion plan—as fast as an alert human driver. That reaction time is on the order of 250msec, and one can imagine current technology evolving to reach that planning speed, albeit at an exorbitant power budget. But we would like to achieve far more than this bare minimum; one of the attractive features of autonomous vehicles is the potential to achieve far greater safety than that achievable by a human driver.  Significantly faster motion planning would translate to much faster reaction times. The difference between reaction times of 250msec1 and 5msec2, for a vehicle traveling at 40mph, is the difference between 15 feet and 0.3 feet traveled before reacting.

Motion planning speed is clearly beneficial for safety, but it offers other important benefits. When motion planning is slow, an AV cannot react quickly to dynamic, non-deterministic agents in its environment, including pedestrians, bicyclists, and other vehicles. When you can’t react quickly, you must move more slowly and more cautiously. Videos of AVs driving in urban environments reveal that they drive slowly and haltingly, having to compensate for their inability to rapidly re-plan.  While such hesitant driving is frustrating to the passenger, it is also likely to aggravate other drivers who are stuck behind the autonomous vehicle or waiting for it to navigate a four-way stop. Aggravating the driving public is dangerous for business, particularly if the driving public clamors for legislation to restrict current hesitant-based driving AVs.

The need for motion planning is clear and our final blog in this series explains how we are making this possible.

RTR AV-Stack

¹250ms is the average human reaction time to the visual stimulus, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4456887/
²Realtime Robotic’s AV motion planner can plan in 1ms, an additional 4 ms is taken to receive and process sensor data.

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Realtime Robotics Introduces RapidPlan and RapidSense Solutions Enabling Faster, More Capable Robots With Real-Time Motion Planning

Posted on by Erin

Makes Robots Do Real Work, Real Fast, in the Real World

AUTOMATE – Chicago – (Apr. 10th, 2019) – Realtime Robotics, Inc. announced today the immediate availability of its collision-free motion planning solutions that make it possible for all robots to navigate dynamic environments smoothly, quickly and intuitively. Its RapidPlan and RapidSense solutions harness cutting-edge computer processing and software to enable industrial and collaborative robots to operate safely and collaboratively with people and other robots within workcells. The company will showcase the solutions as part of the Automate Launch Pad Startup Competition, held on Wed., Apr. 10 at 3 pm CT and in the company’s booth, 9649, at McCormick Place.

Today, robots are programmed to move from Point A to Point B along a single, defined path in order to complete a task. When something unexpected happens, such as an object is presented out of alignment, the path is interrupted, or an obstacle interferes with the programmed trajectory, the robot stops working and cannot resume until a person comes to resolve the issue. The loss of production time due to the event itself and the recovery time required to bring the workcell back online is costly.

With the release of RapidPlan and RapidSense, Realtime Robotics eliminates this constraint by giving robots the ability to recognize and respond to changing environments. The result: manufacturers automate more tasks, more efficiently.

RapidPlan combines a hardware motion planning accelerator (MPA) with a software-based roadmap generation toolkit and is shipping now. It is robot-arm and sensor agnostic and can be integrated into new and existing workcells to drastically improve the safety and performance of both industrial and collaborative robots.

With RapidPlan’s unique combination of hardware and software, automation engineers in manufacturing and distribution operations gain unprecedented flexibility to create workcells for robots that reflect the realities of the environments in which they work. Using a highly intuitive interface, users can load as many as 20 million motions into the MPA. Once stored, RapidPlan can evaluate up to 800,000 motions at 30 frames-per-second in order to ensure that a robot continues to work regardless of interruption.

The company also announced the beta release of RapidSense, an advanced solution that enables robots to “see” everything within a workcell.  The solution’s Calibration tool is a user-friendly interface that can autonomously calibrate as many as 10 depth-sensing cameras, vastly reducing setup and the reconfiguration time required when deploying vision systems.  Once running, RapidSense sends data gathered with the cameras seamlessly to RapidPlan, making it possible for robots to dynamically replan to avoid a person, another robot, or an object that moves into the workspace.

Together, RapidPlan and RapidSense allow people and multiple robots to work collaboratively and cooperatively within the same workcell, without the need for expensive safety systems or time-consuming programming efforts.

“Automation professionals know that more automation is the key to increasing productivity and lowering costs; they also know that today’s robots are limited in terms of speed and safety… Our collision-free motion planning solutions allow robots to perform safely in dynamic, unstructured, and collaborative workspaces, while instantaneously reacting to changes as they occur.”

— Peter Howard, CEO, Realtime Robotics

About Realtime Robotics

Realtime Robotics, Inc.’s responsive motion planning eliminates a huge challenge on the evolutionary path for robots and autonomous vehicles: the constraining trade-off between speed and safety. Its innovative products, RapidPlan and RapidSense, harness next-generation computer processors and software that make it possible for robots and autonomous vehicles to evaluate alternative scenarios and choose the optimal path to avoid collisions – all within milliseconds.

The company was founded in 2016, by Duke University professors Dan Sorin, George Konidaris, and top researchers Sean Murray and Will Floyd-Jones, based on groundbreaking DARPA-funded research in motion planning. Based in Boston, the company’s early investors include Sparx Group Co., Ltd., Toyota AI, and Scrum Ventures. More information about Realtime Robotics, its technology, and the business benefits it offers can be found on our website.

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Solving the Autonomous Vehicles Motion Planning Conundrum

Posted on by Erin

Our last blog explained the importance of motion planning for the adoption of AV. In this post, we’ll discuss how Realtime Robotics is enabling normal autonomous driving in urban environments.

Electronics Board

Realtime Robotics has developed its own, special-purpose computer processor for AV motion planning to address the critical need for super-fast motion planning.  This custom-designed processor is tailored to perform motion planning at rates of hundreds to thousands of times per second. The speed advantage of our processor, compared to commodity processors, derives from its sole focus on motion planning; all of its hardware resources and all of its power budget are devoted to motion planning.  The concept of special-purpose processors is not new—graphics processors (GPUs) and bitcoin mining processors are two notable examples—but Realtime Robotics has created the first motion planning processor.

The tremendous speed of the Realtime Robotics motion planning processor enables ultra-fast reaction times and is, in fact, faster than needed simply to react.  There is relatively little difference between reaction times of 5msec and 10msec (0.3 vs 0.6 feet traveled at 40mph). Nevertheless, the ability to plan faster than necessary to react enables an exciting new feature: risk-aware motion planning.

Risk-aware motion planning considers multiple possible behaviors of the non-deterministic agents in the environment and determines a motion plan that minimizes risk given these uncertain behaviors.  Consider a reaction time goal of 10msec. Our motion planner can compute multiple motion plans in that time, and each of those plans can consider different possible behaviors of the other agents. Faster planning enables more plans to be computed per reaction time epoch, thus increasing the range of possible behaviors considered.  This risk-aware planning is analogous to how humans drive. When, for example, we see a bicyclist on our right, we drive far enough away from her to accommodate the risk of her veering to her left, and we subconsciously compute this risk based on a mental model of bicyclist behavior that is informed by prior experiences.

If autonomous vehicles are to fulfill their promise of relieving the tedium of driving and drastically improve the safety of our roads, they will need to be able to deal with the complexity of decision-making in the real world. Realtime’s specialized motion planning processor offers a path to defeating the key remaining obstacle to achieving this vision, leading to autonomous vehicles that react instantly, and that can deal with the uncertainty inherent in complex driving scenarios like the busy urban and suburban streets that you and I navigate every day.

RTR AV-Stack-Bicyclist

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Realtime “Graduates” from MassRobotics

Posted on by Erin

Realtime Robotics “graduated” from the MassRobotics incubator late last year. Not-for-profit MassRobotics is a Boston-based workspace for robotics companies to collaborate, build and innovate. Realtime Robotics originally headquartered in MassRobotics as it provided a reasonably priced, centrally located office and lab space that offered the flexibility to grow with their project needs and infrastructure requirements.

“MassRobotics is a perfect place for a robotics startup to launch from,” said Peter Howard, CEO of Realtime Robotics. “We had access to a flexible workspace, like-minded people to bounce ideas off of, robots and hardware without consuming our limited funds, and invaluable connections to customers, investors, advisors, researchers, and events that linked us to incredible employees and partnerships. We would definitely not have made the rapid progress we have achieved had we not had the amazing resources that come with being a MassRobotics member.”

Realtime Robotics moved their headquarters to nearby Tower Point in the Fort Point district of Boston. They currently have 30 full-time employees, most of which you can see here in their new space:

Team-600x400

Learn more about MassRobotics.

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