PASADENA, Calif. — COAST Autonomous today announced that Harbor Rail Services of California has selected it to deploy self-driving vehicles at the Kinney County Railport in Texas.
This groundbreaking collaboration is the first deployment of self-driving vehicles at a U.S. rail yard, said the companies. Harbor Rail and COAST teams have identified a number of areas where autonomous vehicles can add value, including staff transportation, delivery of supplies and equipment, perimeter security, and lawn mowing.
COAST Autonomous is a software and technology company focused on delivering autonomous vehicle (AV) solutions at appropriate speeds for urban and campus environments. COAST said its mission is to build community by connecting people with mobility solutions that put pedestrians first and give cities back to people.
COAST has developed a full stack of AV software that includes mapping and localization, robotics and artificial intelligence, fleet management and supervision systems. Partnering with proven manufacturers, COAST said it can provide a variety of vehicles equipped with its software to offer Mobility-as-a-Service (MaaS) to cities, theme parks, campuses, airports, and other urban environments.
The company said its team has experience and expertise in all aspects of implementing and operating AV fleets while prioritizing safety and the user experience. Last year, the company conducted a demonstration in New York’s Times Square.
Harbor Rail operates railcar repair facilities across the U.S., including the Kinney County Railport (KCRP), a state-of-the-art railcar repair facility that Harbor Rail operates near the U.S.-Mexico border. KCRP is located on 470 acres of property owned by Union Pacific, the largest railroad in North America. The facility prepares railcars to meet food-grade guidelines, so they are ready to be loaded with packaged beer in Mexico and return to the U.S. with product for distribution.
COAST completes mapping, ready to begin service
COAST has completed 3D mapping of the facility, a first step in any such deployment, and the first self-driving vehicle is expected to begin service at KCRP next month.
“Through the introduction of re-designed trucks, innovative process improvements and adoption of data-driven KPIs [key performance indicators], Harbor Rail successfully reduced railcar rejections rates from 30% to 0.03% in KCRP’s first year of operations,” said Mark Myronowicz, president of Harbor Rail. “However, I am always looking for ways to improve our performance and provide an even better service for our customers.”
Source: COAST Autonomous
“At a large facility like KCRP, we have many functions that I am convinced can be carried out by COAST vehicles,” Myronowicz said. “This will free up additional labor to work on railcars, make us even more efficient, help keep the facility safe at night, and even cut the grass when most of us are asleep. This is a fantastic opportunity to demonstrate Harbor Rail’s commitment to being at the forefront of innovation and customer service.”
“This is an exciting moment for COAST, and we are looking forward to working with Harbor Rail’s industry-leading team,” said David M. Hickey, chairman and CEO of COAST Autonomous. “KCRP is exactly the type of facility that will show how self-driving technology can improve efficiency and cut costs.”
“While the futuristic vision of driverless cars has grabbed most of the headlines, COAST’s team has been focused on useful mobility solutions that can actually be deployed and create tremendous value for private sites, campuses, and urban centers,” he said. “Just as railroads are often the unsung heroes of the logistics industry, COAST’s vehicles will happily go about their jobs unnoticed and quietly change the world.”
ALBEMARLE COUNTY, Va. — Perrone Robotics Inc., in partnership with Albemarle County and JAUNT Inc., last week announced that Virginia’s first public autonomous shuttle service began pilot operations in Crozet, Va.
The shuttle service, called AVNU for “Autonomous Vehicle, Neighborhood Use,” is driven by Perrone Robotics’ TONY (TO Navigate You) autonomous shuttle technology applied to a Polaris Industries Inc. GEM shuttle. Perrone Robotics said its Neighborhood Electric Vehicle (NEV) shuttle has industry-leading perception and guidance capabilities and will drive fully autonomously (with safety driver) through county neighborhoods and downtown areas on public roads, navigating vehicle, and pedestrian traffic. The base GEM vehicle meets federal safety standards for vehicles in its class.
“With over 33,000 autonomous miles traveled using our technology, TONY-powered vehicles bring the highest level of autonomy available in the world today to NEV shuttles,” said Paul Perrone, founder/CEO of Perrone Robotics. “We are deploying an AV platform that has been carefully refined since 2003, applied in automotive and industrial autonomy spaces, and now being leveraged to bring last-mile services to communities such as those here in Albemarle County, Va. What we deliver is a platform that operates shuttles autonomously in complex environments with roundabouts, merges, and pedestrian-dense areas.”
The TONY-based AVNU shuttle will offer riders trips within local residential developments, trips to connect neighborhoods, and connections from these areas to the downtown business district.
After the pilot phase, additional routes will be demonstrate Albemarle County development initiatives such as connector services for satellite parking. They will also connection with JAUNT‘s commuter shuttles, also targeted for autonomous operation with TONY technology.
“We have seen other solutions out there that require extensive manual operation for large portions of the course and very low speeds for traversal of tricky sections,” noted Perrone. “We surpass these efforts by using our innovative, super-efficient, and completely novel and patented autonomous engine, MAX®, that has over 16 years of engineering and over 33,000 on and off-road miles behind it. We also use AI, but as a tool, not a crutch.”
“It is with great pleasure that we launch the pilot of the next generation of transportation — autonomous neighborhood shuttles — here in Crozet,” said Ann Mallek, White Hall District Supervisor. “Albemarle County is so proud to support our home town company, Perrone Robotics, and work with our transit provider JAUNT, through Smart Mobility Inc., to bring this project to fruition.”
Perrone said that AVNU is electrically powered, so the shuttle is quiet and non-polluting, and it uses solar panels to significantly extend system range. AVNU has been extensively tested by Perrone Robotics, and testing data has been evaluated by Albemarle County and JAUNT prior to launch.
Using processed images, algorithms learn to recognize the real environment for autonomous driving. Source: understand.ai
Autonomous cars must perceive their environment accurately to move safely. The corresponding algorithms are trained using a large number of image and video recordings. Single image elements, such as a tree, a pedestrian, or a road sign must be labeled for the algorithm to recognize them. Understand.ai is working to improve and accelerate this labeling.
Understand.ai was founded in 2017 by computer scientist Philip Kessler, who studied at the Karlsruhe Institute of Technology (KIT), and Marc Mengler.
“An algorithm learns by examples, and the more examples exist, the better it learns,” stated Kessler. For this reason, the automotive industry needs a lot of video and image data to train machine learning for autonomous driving. So far, most of the objects in these images have been labeled manually by human staffers.
“Big companies, such as Tesla, employ thousands of workers in Nigeria or India for this purpose,” Kessler explained. “The process is troublesome and time-consuming.”
Accelerating training at understand.ai
“We at understand.ai use artificial intelligence to make labeling up to 10 times quicker and more precise,” he added. Although image processing is highly automated, final quality control is done by humans. Kessler noted that the “combination of technology and human care is particularly important for safety-critical activities, such as autonomous driving.”
The labelings, also called annotations, in the image and video files have to agree with the real environment with pixel-level accuracy. The better the quality of the processed image data, the better is the algorithm that uses this data for training.
“As training images cannot be supplied for all situations, such as accidents, we now also offer simulations based on real data,” Kessler said.
Although understand.ai focuses on autonomous driving, it also plans to process image data for training algorithms to detect tumors or to evaluate aerial photos in the future. Leading car manufacturers and suppliers in Germany and the U.S. are among the startup’s clients.
The startup’s main office is in Karlsruhe, Germany, and some of its more than 50 employees work at offices in Berlin and San Francisco. Last year, understand.ai received $2.8 million (U.S.) in funding from a group of private investors.
In 2012, Kessler started to study informatics at KIT, where he became interested in AI and autonomous driving when developing an autonomous model car in the KITCar students group. Kessler said his one-year tenure at Mercedes Research in Silicon Valley, where he focused on machine learning and data analysis, was “highly motivating” for establishing his own business.
“Nowhere else can you learn more within a shortest period of time than in a startup,” said Kessler, who is 26 years old. “Recently, the interest of big companies in cooperating with startups increased considerably.”
He said he thinks that Germany sleepwalked through the first wave of AI, in which it was used mainly in entertainment devices and consumer products.
“In the second wave, in which artificial intelligence is applied in industry and technology, Germany will be able to use its potential,” Kessler claimed.
CloudMinds was among the robotics companies receiving funding in March 2019. Source: CloudMinds
Investments in robots, autonomous vehicles, and related systems totaled at least $1.3 billion in March 2019, down from $4.3 billion in February. On the other hand, automation companies reported $7.8 billion in mergers and acquisitions last month. While that may represent a slowdown, note that many businesses did not specify the amounts involved in their transactions, of which there were at least 58 in March.
Self-driving cars and trucks — including machine learning and sensor technologies — continued to receive significant funding. Although Lyft’s initial public offering was not directly related to autonomous vehicles, it illustrates the investments flowing for transportation.
Other use cases represented in March 2019 included surgical robotics, industrial automation, and service robots. See the table below, which lists amounts in millions of dollars where they were available:
Company
Amt. (M$)
Type
Lead investor, partner, acquirer
Date
Technology
Airbiquity
15
investment
Denso Corp., Toyota Motor Corp., Toyota Tsushu Corp.
March 12, 2019
connected vehicles
AROMA BIT Inc.
2.2
Series A
Sony Innovation Fund
March 3, 2019
olofactory sensors
AtomRobot
Series B1
Y&R Capital
March 5, 2019
industrial automation
Automata
7.4
Series A
ABB
March 19, 2019
robot arm
Avidbots
23.6
Series B
True Ventures
March 21, 2019
commercial floor cleaning
Boranet
Series A
Gobi Partners
March 6, 2019
IIoT, machine vision
Broadmann17
11
Series A
OurCrowd
March 6, 2019
deep learning, autonomous vehicles
Cloudminds
300
investment
SoftBank Vision Fund
March 26, 2019
service robots
Corindus
4.8
private placement
March 12, 2019
surgical robot
Determined AI
11
Series A
GV (Google Ventures)
March 13, 2019
AI, deep learning
Emergen Group
29
Series B
Qiming Venture Partners
March 13, 2019
industrial automation
Fabu Technology
pre-Series A
Qingsong Fund
March 1, 2019
autonomous vehicles
Fortna
recapitalization
Thomas H. Lee PArtners LP
March 27, 2019
materlais handling
ForwardX
14.95
Series B
Hupang Licheng Fund
March 21, 2019
autonomous mobile robots
Gaussian Robotics
14.9
Series B
Grand Flight Investment
March 20, 2019
cleaning
Hangzhou Guochen Robot Technology
15
Series A
Hongcheng Capital, Yingshi Fund (YS Investment)
March 13, 2019
robotics R&D
Hangzhou Jimu Technology Co.
Series B
Flyfot Ventures
March 6, 2019
autonomous vehicles
InnerSpace
3.2
seed
BDC Capital's Women in Technology Fund
March 26, 2019
IoT
Innoviz Technologies
132
Series C
China Merchants Capital, Shenzhen Capital Group, New Alliance Capital
March 26, 2019
lidar
Intelligent Marking
investment
Benjamin Capital
March 6, 2019
autonomous robots for marking sports fields
Kaarta Inc.
6.5
Series A
GreenSoil Building Innovation Fund
March 21, 2019
lidar mapping
Kolmostar Inc.
10
Series A
March 5, 2019
positioning technology
Linear Labs
4.5
seed
Science Inc., Kindred Ventures
March 26, 2019
motors
MELCO Factory Automation Philippines Inc.
2.38
new division
Mitsubishi Electric Corp.
March 12, 2019
industrial automation
Monet Technologies
4.51
joint venture
Honda Motor Co., Hino Motors Ltd., SoftBank Corp., Toyota Motor Corp
Bonfire Ventures, Vertex Ventures, London Venture Partners
March 11, 2019
machine vision
Vtrus
2.9
investment
March 8, 2019
drone inspection
Weltmeister Motor
450
Series C
Baidu Inc.
March 11, 2019
self-driving cars
And here are the mergers and acquisitions:
March 2019 robotics acquisitions
Company
Amt. (M$)
Acquirer
Date
Technology
Accelerated Dynamics
Animal Dynamics
3/8/2019
AI, drone swarms
Astori AS
4Subsea
3/19/2019
undersea control systems
Brainlab
Smith & Nephew
3/12/2019
surgical robot
Figure Eight
175
Appen Ltd.
3/10/2019
AI, machine learning
Floating Point FX
CycloMedia
3/7/2019
machine vision, 3D modeling
Florida Turbine Technologies
60
Kratos Defense and Security Solutions
3/1/2019
drones
Infinity Augmented Reality
Alibaba Group Holding Ltd.
3/21/2019
AR, machine vision
Integrated Device Technology Inc.
6700
Renesas
3/30/2019
self-driving vehicle processors
Medineering
Brainlab
3/20/2019
surgical
Modern Robotics Inc.
0.97
Boxlight Corp.
3/14/2019
STEM
OMNI Orthopaedics Inc.
Corin Group
3/6/2019
surgical robotics
OrthoSpace Ltd.
220
Stryker Corp.
3/14/2019
surgical robotics
Osiris Therapeutics
660
Smith & Nephew
3/12/2019
surgical robotics
Restoration Robotics Inc.
21
Venus Concept Ltd.
3/15/2019
surgical robotics
Sofar Ocean Technologies
7
Spoondrift, OpenROV
3/28/2019
underwater drones, sensors
Torc Robotics Inc.
Daimler Trucks and Buses Holding Inc.
3/29/2019
driverless truck software
Surgical robots make the cut
One of the largest transactions reported in March 2019 was Smith & Nephew’s purchase of Osiris Therapeutics for $660 million. However, some Osiris shareholders are suing to block the acquisition because they believe the price that U.K.-based Smith & Nephew is offering is too low. The shareholders’ confidence reflects a hot healthcare robotics space, where capital, consolidation, and chasing new applications are driving factors.
Venus Concept Ltd. merged with hair-implant provider Restoration Robotics for $21 million, and Shanghai Changren Information Technology raised Series A funding of $14.89 million for its Xiaobao healthcare robot.
Aside from Lyft, the biggest reported transportation robotics transaction in March 2019 was Renesas’ completion of its $6.7 billion purchase of Integrated Device Technology Inc. for its self-driving car chips.
The next biggest deal was Weltmeister Motor’s $450 million Series C, in which Baidu Inc. participated.
Lidar also got some support, with Innoviz Technologies raising $132 million in a Series C round, and Ouster raising $60 million. In a prime example of how driverless technology is “paying a peace dividend” to other applications, Google parent Alphabet’s Waymo unit offered its custom lidar sensors to robotics, security, and agricultural companies.
Automakers recognize the need for 3-D modeling, sensors, and software for autonomous vehicles to navigate safely and accurately. A Daimler unit acquired Torc Robotics Inc., which is working on driverless trucks, and CycloMedia acquired machine vision firm Floating Point FX. The amounts were not specified.
Speaking of machine learning, Appen Ltd. acquired dataset annotation company Figure Eight for $175 million, with an possible $125 million more based on 2019 performance. Denso Corp. and Toyota Motor Corp. contributed $15 million to Airbiquity, which is working on connected vehicles.
Service robots clean up
From retail to cleaning and customer service, the combination of improving human-machine interactions, ongoing staffing turnover and shortages, and companies with round-the-clock operations has contributed to investor interest.
The SoftBank Vision Fund participated in a $300 million round for CloudMinds. The Chinese AI and robotics company’s XR-1 is a humanoid service robot, and it also makes security robots and connects robots to the cloud.
According to its filing with the U.S. Securities and Exchange Commission, TakeOff Technologies Inc. raised an unspecified amount for its grocery robots, an area that many observers expect to grow as consumers become more accustomed to getting home deliveries.
On the cleaning side, Avidbots raised $23.6 million in Series B, led by True Ventures. Gaussian Robotics’ Series B was $14.9 million, with participation from Grand Flight Investment.
China’s efforts to develop its domestic robotics industry continued, as Emergen Group’s $29 million Series B round was the largest reported investment in industrial automation last month.
Hangzhou Guochen Robot Technology raised $15 million in Series A funding for robotics research and development and integration.
Data startup Spopondrift and underwater drone maker OpenROV merged to form Sofar Ocean Technologies. The new San Francisco company also announced a Series A round of $7 million. Also, 4Subsea acquired underwater control systems maker Astori AS.
In the aerial drone space, Kratos Defense and Security Solutions acquired Florida Turbine Technologies for $60 million, and Vtrus raised $2.9 million for commercializing drone inspections. Kaarta Inc., which makes a lidar for indoor mapping, raised $6.5 million.
The Robot Reportbroke the news of Aria Insights, formerly known as CyPhy Works, shutting down in March 2019.
Editors Note: What defines robotics investments? The answer to this simple question is central in any attempt to quantify robotics investments with some degree of rigor. To make investment analyses consistent, repeatable, and valuable, it is critical to wring out as much subjectivity as possible during the evaluation process. This begins with a definition of terms and a description of assumptions.
Investors and Investing
Investment should come from venture capital firms, corporate investment groups, angel investors, and other sources. Friends-and-family investments, government/non-governmental agency grants, and crowd-sourced funding are excluded.
Robotics and Intelligent Systems Companies
Robotics companies must generate or expect to generate revenue from the production of robotics products (that sense, think, and act in the physical world), hardware or software subsystems and enabling technologies for robots, or services supporting robotics devices. For this analysis, autonomous vehicles (including technologies that support autonomous driving) and drones are considered robots, while 3D printers, CNC systems, and various types of “hard” automation are not.
Companies that are “robotic” in name only, or use the term “robot” to describe products and services that that do not enable or support devices acting in the physical world, are excluded. For example, this includes “software robots” and robotic process automation. Many firms have multiple locations in different countries. Company locations given in the analysis are based on the publicly listed headquarters in legal documents, press releases, etc.
Verification
Funding information is collected from a number of public and private sources. These include press releases from corporations and investment groups, corporate briefings, and association and industry publications. In addition, information comes from sessions at conferences and seminars, as well as during private interviews with industry representatives, investors, and others. Unverifiable investments are excluded.
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