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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.
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Trends with an above average number of articles over the last 12 months, but declining or low growth compared to 12 months before
Trends with a low number of articles over the last 12 months, and declining or low growth compared to 12 months before.
Trends with an above average number of articles over the last 12 months, which is even higher than 12 months before.
Trends with a low number of articles over the last 12 months, but with a high growth compared to 12 months before.
Timeframe: 2018 – 2019For comprehensibility values for volume and growth are standardized and normalized (values from 0-100).
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.
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.
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.
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)
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.
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)
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.
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)
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.
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)
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.
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.
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.
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 比特币交易价格行情home being freed of time-consuming household chores.
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.
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.
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.
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.
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.
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