Sonar Research on Autonomous Things

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What's Next?

With SONAR Trend Platform, Reply is able to create an overview and mapping of relevant trends related to ”Autonomous Things”, based on their occurrence within expert media articles, mass media, patents and scientific publications.
Discover more about Reply's survey on current developments in the field of Automation and Autonomy!

HOW AUTONOMOUS IS THE WORLD RIGHT NOW?

Progress in AI has spurred a number of Autonomous Things (ATs) such as drones, robots and vehicles for tasks previously performed by humans. While autonomous household appliances are widely commercialized, autonomous cars or passenger drones are at least a decade away from large-scale introduction.

With significant advances in enabling technologies such as AI, Lidar, Computer Vision and 5G, Autonomous Technology is expected to evolve from stand-alone solutions to a complex swarm of collaborative intelligent systems that master unstructured surroundings.

Level 0

Level 1

Level 2

Level 3

Level 4

Level 5

AUTONOMOUS
VEHICLES

Houdina Radio Control
demonstrates a radio-controlled
"driverless" car (1925)

VaMP AV drives
(almost) completely
autonomous for
2,000 km (1995)

Darpa Self-
Driving Car
Grand
Challange
(2004)

Tesla releases-
its Autopilot
software update
(2015)

Level 4
Autonomy
expected
(2020-22)

The earliest forecast
for driving fully
autonomous (2030)

"Phantom Auto"
demonstration in
Milwaukee (1926)

First truly automated car
developed by Japan's
Tsukuba Mechanical
Engineering Laboratory
(1977)

First self-driving
car goes for a
test drive (1986)

Start of Google
Self-Driving project
Waymo (2009)

Launch of first
Level 3 Autonomy
car Audi A8 (2017)

33 million
autonomous
vehicles will be
sold globally
(2040)

1920

1930

1940

1950

1960

1970

1980

1990

2000

2010

2020

2030

ROBOTS
& DRONES

Term "Robot"
first used by
Czech writer
Karel Capek
(1921)

Alan Turing
develops
Turing Test
(1950)

SRI develops
mobile robot
"Shakey" (1966)

Robot "Kismet"
interacts emotionally
with humans (1998)

Autonomous vacuum
cleaners iRobot and
Electrolux (2002)

First drone delivery
by Amazon (2016)

Uber Elevate is planning shared
air transportation between and
within cities (2023)

William Grey
Walter develops
first autonomous
robot (1948)

First digitally
operated and
programmable
robot (1954)

The first service
robot "HelpMate"
begins work at
Danbury Hospital
(1988)

NASA
deploys first
autonomous
robotic system
"Sojourner" on
Mars surface
(1997)

Honda releases
humanoid robot
"Asimo" (2000)

Robot demonstrates
self-awareness (2015)

Wing Aviation is the first
unmanned airline in the
US (2019)

40 of the world's
largest economies
permit routinely
operated autonomous
drones (2022)

MOVING FROM AUTOMATION TO AUTONOMY

Supported by Artificial Intelligence and Machine Learning, autonomous technologies enable things to move and interact freely without active physical control or supervision by a human operator. The technology is still in the development stage, but rapid advances are driving a growing global market. The following five levels of autonomy describe the extent to which technology is already taking over tasks and responsibilities from human operators:

Level 1

Assistance

The machine is mainly controlled by operators and provides assistance features.

Level 2

Partial Automation

The machine has automated functions, but the operator has to stay engaged and monitor the processes at all times.

Level 5

Fully Autonomous

The machine is able to decide and act independently of humans.

Level 4

High Automation

The machine is able to perform all functions under certain conditions. An operator may have the option to control.

Level 3

Conditional Automation

An operator must be present, but he is not required to monitor processes - however, he must be able to take control with notice.

Click on the legend labels to select/deselect.

ESTABLISHED
TRENDS

Trends with an above average number of articles over the last 12 months, but declining or low growth compared to 12 months before

NICHE
TRENDS

Trends with a low number of articles over the last 12 months, and declining or low growth compared to 12 months before.

BOOMING
TRENDS

Trends with an above average number of articles over the last 12 months, which is even higher than 12 months before.

UPCOMING
TRENDS

Trends with a low number of articles over the last 12 months, but with a high growth compared to 12 months before.

Growth Volume

Timeframe: 2018 – 2019
For comprehensibility values for volume and growth are standardized and normalized (values from 0-100).

The arrow in the illustration above implies a typical trend development and a life cycle from a small and growing trend – which is discussed in relatively few scientific articles and publications – to a larger, established trend with stagnating growth, which has long been discussed in various media and has shifted from niche circles into the mainstream.

IN-DEPTH SENSING BY ENHANCED SENSOR & CAMERA SYSTEMS

Technological advances and cost reductions in sensors, actuators, radar, lidar and camera systems, as well as advances in multi-sensor integration through sensor fusion, improve depth detection for safe and automated motion and bring autonomous things closer to reality.
DECISION MAKING ENABLED BY INTELLIGENT TECHNOLOGY

Rapid advances in fields like AI, ML and Deep Neural Networks are creating the conditions for truly intelligent machines that can navigate autonomously. AT investments have recently been dominated by AI tech to overcome the remaining hurdles to full autonomy.
THE NEXT GENERATION OF PROCESSING CAPACITIES

Autonomous things collect huge amounts of data, especially driverless vehicles: they are expected to generate 4 TB of data each day. The next generation of supercomputers and the expansion of 5G networks are important prerequisites for processing data in real time and making quick decisions.

Things that are becoming autonomous

Technology that makes things autonomous

Things that are becoming autonomous

1.AUTONOMOUS ROBOTS & DRONES

Progress in AI and navigation technology is leading to a new generation of autonomous robots and UAVs being increasingly commercialized in indoor and outdoor environments and applications such as retail, security and inspection, agriculture, delivery, transportation and warehouse management. Robots are changing fundamentally: they are becoming intelligent, mobile and able to interact and collaborate with a human counterpart. Especially, the area of autonomous mobile robots is experiencing enormous growth, mainly due to increasing e-commerce and the need to optimise warehouse capacity and efficiency. This is why delivery drones also generated a lot of attention last year, most notably when Project Wing received approval to operate the first commercial air delivery services in Australia and the US, although conditional automation remains a legal requirement for drone operations.

These were the top trending players, led by autonomous delivery company Nuro, followed by Fanuc, Yaskawa,
Boston Dynamics – lately expanding its business to logistics and warehouse robots – and ABB.

Autonomous mobile robots have been shipped globally in 2018. The forecast by 2022: 350.000. (Interact Analysis)

WHAT‘S COMING UP

Continental – Four legged delivery: Autonomtive supplier Continental presented at CES 2019 its vision of seamless and automated future parcel delivery: a mini-sized autonomous electric pod paired with autonomous and electric dog-like four-legged robots to handle the last mile of package delivery.

DroneSeed – Precision Forestry: The Seattle-based start-up DroneSeed uses drones, automation and machine learning to work in post-fire environments replanting vegetation and combat the spread of wildfires using drone swarms and spray to protect them. It is the first and currently only company that received FAA approval for heavy lift UAV operation and swarm spraying.

2.DRIVERLESS VEHICLE TRANSPORTATION

Autonomous mobility is picking up speed with a new breed of transport-as-a-service offerings in various test regions: commercial robo-taxis starting operations, as well as short-distance delivery bots and autonomous food delivery services. The emergence of these new services – mostly driven by big players from the high-tech, automotive, shipping and food industries – leads to a high media presence, while slow-moving shuttle services in strictly geographical areas start to establish themselves more quietly. Through investments, the area of autonomous trucking is growing. In addition, a new type of vehicle is emerging: Specially developed vehicles whose cabin design is geared to new on-demand mobility-as-a-service concepts.

Robotaxis will increase shared travel service revenues from $5 to $285 bn in 2030. (Goldman Sachs, May 2017)

Commuting hours per year freed by self-driving vehicles (Intel, June 2017)

WHAT’S COMING UP

May Mobility – slow self-driving Shuttles: The autonomous vehicle start-up May Mobility is racing to deploy autonomous vehicles at commercial scale. It was founded two years ago and since than has developed low-speed autonomous shuttles that already run along specific routes in cities across the U.S. Midwest. After receiving a $22M investment the company is currently planning for nationwide expansion.

TuSimple – Autonomous Trucking: Autonomous trucking startup TuSimple is running three to five fully autonomous commercial trips on a daily basis for 12 contracted customers in Arizona. The startup plans to scale up its fleet to 50 trucks and extend deliveries to Texas. It has therefore recently raised $95M in Series D funding round.

Technology that makes things autonomous

1.LIDAR AND RADAR TECHNOLOGIES

Despite the remarkable progress made in recent years, there are still some technological hurdles that need to be overcome within the autonomous core technologies around sensing, mapping and processing: In the field of hardware, a fierce battle for efficiency and cost reduction is being fought: solid-state lidar solutions are gaining in importance as they are cheaper, faster and higher resolution (a price below $250 per unit will soon be reached) – whereas some approaches question the need for lidar in general. In radar technology, the current focus is on high-resolution 4D solutions that promise higher accuracy at lower cost. In addition to the network capacity needed to handle the massive amounts of data, software solutions are needed to meet the increasing functional requirements. But above all there is the challenge of cyber security.

Lidar startup Ouster raises $460M

Lidar market forecast in five years (VentureBeat, March 2019)

The amount of money OTA updates and prognostics can save ridesharing services. (ABI Research, Q2 2018)

WHAT’S COMING UP

Aeva – 4D Lidar: Silicon Valley newcomer Aeva started by Soroush Salehian and Mina Rezk, has developed a high-resolution, real-time velocity “4D lidar” solution. Aeva’s sensors emit a continuous low-power laser, which allows them to sense instant velocity of every point in the frame at ranges up to 300 meters. In 2018 they received a $45M funding and in early 2019 started working with Audi-supported Autonomous Intelligent Driving.

Realtime Robotics – Ultrafast Motion Planning: Realtime Robotics next-generation computer processor “RapidPlan” and software should provide fast, collision-free motion planning solutions to enable robots, autonomous vehicles and other machines to navigate dynamic and unstructured environments quickly and intuitively. The processor is currently able to solve motion planning in under a millisecond for roadmaps of under 3000 edges.

2.ENABLING NEXT LEVEL AUTONOMY

In addition to the regulatory environment, technology standards and a suitable intelligent infrastructure, advances in core technologies such as AI, ML, 5G, Blockchain, Cloud and Edge Computing are a prerequisite for an autonomous future. On the way to full autonomy, contextual AI and machine learning skills in particular are indispensable building blocks for perception, prediction and self-sufficient decision making and currently attract the highest funding volumes in the field of autonomous technology. The expansion of 5G networks - with constant and reliable high-speed data transmission - is on the advance, with the first commercial networks being switched live in both the USA and South Korea.

After just 20 hours of training, Wayve’s fast-learning AI car is already driving itself on unfamiliar roads

>40% of the world’s population will be reached by 5G by the end of 2024. (Ericsson, November 2018)

WHAT’S COMING UP

Stocked Robotics – AI in a Box: Stocked Robotics is transforming manually-driven forklifts and industrial vehicles within two hours’ time into swarms of autonomous forklifts using its AI-powered Stocked Intelligence Engine for Robot Automation (SIERA) platform. It claims to be the only company offering infrastructure-free end-to-end forklift automation.

Uber & GM Cruise – Open Source AV Virtualization: Uber and GM Cruise have been opening up their visualization software on the web, making it free for anyone to use. The visualization system allows engineers to break out and play back certain trip intervals for closer inspection. Many AV operators rely on off-the-shelf visualization systems not designed with self-driving cars in mind.

COST REDUCTION AND INCREASING EFFICIENCY

Autonomous things will increasingly take over repetitive, dangerous and to a certain degree intelligent labor previously conducted by human workforce, reducing costs while increasing output, e.g. due to 24/7 operations, AI-based real-time decision making and optimization. Moreover, workers will be increasingly supported by autonomous cobots working hand in hand with them.

Examples:
By the time autonomous transportation is arriving, transportation services will be getting cheaper for passengers due to better capacity utilization and routing optimization. Autonomous vehicle utilization might be further optimized by shifting the main purpose of the journeys based on demand– e.g. from moving around people to delivering goods during off-peak travel times.

FREEING UP TIME OF CUSTOMERS AND EMPLOYEES

Autonomous things will free up tremendous amounts of human time – in the private as well as business life. People can spend the freed time differently, opening up business opportunities for new products and services providing an enhanced customer experience e.g. during travelling, work or at home being freed of time-consuming household chores.

Examples:
Autonomous mobility services offering convenient and on-demand door-to-door services with purpose-driven vehicles depending on how customers need to spend the travelling time best e.g. sleeping for long-distance journeys, on-board entertainment, dining facilities, on-board office, training and health tracking, or personal wellness space.

COMPENSATING LABOR SHORTAGES & NEW SKILL DEMAND

Increasingly sophisticated autonomous mobile robots, drones and vehicles represent a way to compensate for labor shortages in certain business fields but also will displace jobs with a high level of routine (e.g. loading and unloading). More intelligent labor will follow due to data-driven and AI tech. Job profiles will have to transform towards more advanced and soft skills.

Examples:
Driverless agricultural equipment might pose a possibility to curtail labor shortages on farms, e.g. during harvesting season. Also the shipping sector is facing increasing amounts of cargo and a looming labor shortage, which might be tackled by autonomous vessels. In production facilities humans might only have to deal with errors that autonomous systems aren’t capable of dealing with.

RISE OF AUTONOMY-AS-A-SERVICE BUSINESS MODELS

Companies with little experience in automation as well as limited resources for buying autonomous equipment will be able to take advantage of an increasing number of service providers offering fully automated and unmanned systems as a service, taking over the installation, management and maintenance of autonomous workforces.

Examples:
Autonomous robots, drones or vehicles can be leased or rented for various tasks like cleaning, shipping, inspections, security, warehouse operations, transportation etc. even for smaller companies where ownership of automation equipment today has proved to be economically unviable.

THE ECONOMY OF AUTONOMOUS THINGS

As Autonomous Things are evolving, they will become more and more integrated and intelligently connected with each other as well as the environment. They will be paired with voice technology and emotional intelligence, coexisting and naturally interacting with humans at work or in private lives.

SONAR is an innovative, Data-as-a-Service Tool for quantified foresight. It recognizes, compares and analyzes existing trends, and identifies new developments in real-time.

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AUTONOMOUS THINGS TREND RESEARCH

THE TRANSITION FROM AUTOMATION TO AUTONOMY IS IN FULL SWING