Mercedes-Benz Vans has invested in Starship Technologies, a start-up in the development of ground-based, autonomous delivery robots.
As lead investor, Mercedes-Benz Vans is participating in a 16.5 million euro financing round.
The two companies introduced the so-called mothership concept in September 2016. The concept combines the advantages of a van with those of an autonomous delivery robot. A Sprinter presented as a prototype serves as a mobile loading and transport hub for eight robots.
“Thanks to the intelligent interlinking of delivery processes, it will play a part in significantly improving the efficiency of last-mile delivery logistics in future,” Mercedes-Benz Vans said in a statement. “The mothership concept is the first outcome of a research and development cooperation between Mercedes-Benz Vans and Starship Technologies that began in 2016. Through its financial commitment to Starship Technologies, Mercedes-Benz Vans is now reinforcing this strategic, long-term collaboration.”
The investment, it says, is also in furtherance of its strategic future initiative called adVANce.
“The robot can only travel short distances under its own power and until now has had to return to the warehouse to be reloaded after each delivery”, says Volker Mornhinweg, Head of Mercedes-Benz Vans. “On the one hand, the introduction of the van as a mobile hub widens the operational radius of the robots significantly, while also rendering superfluous the cost-intensive construction and operation of decentralised warehouses.
“We see the combination of these two technologies as an opportunity to give our van customers access to some completely new services and business models. At the same time, we make the delivery process much more convenient for the end customer. For example, the concept makes it much easier to deliver goods to the end customer on time.”
The aim is to develop the concept systematically over the coming months. As the two companies recently announced at CES 2017 in Las Vegas, initial pilot tests for this combination of van and robot are planned for Europe. Following pilot testing of the delivery robots, which has been and continues to be undertaken by Starship Technologies with other partners, the plan is to begin widespread testing of the joint concept with one or several logistics partners. The launch of the pilot project in a real-world environment is scheduled to take place later this year.
Mercedes-Benz Vans presses ahead with the transformation of the transport sector
Mercedes-Benz Vans unveiled its adVANce strategic future initiative last September. The business division is systematically directing its focus at new, quickly changing customer needs, with a particular eye to identifying innovative solutions. The company will invest some 500 million euros in the advancement of digitisation, automation and robotics in vans as well as in innovative mobility offerings until 2020.
“Mercedes-Benz Vans is thus evolving from a globally successful van manufacturer into a supplier of holistic system solutions,” it says.
Project Bloodhound saved
The British project to break the world landspeed record at a site in the Northern Cape has been saved by a new backer, after it went into bankruptcy proceedings in October.
Two weeks ago, and two months after entering voluntary administration, the Bloodhound Programme Limited announced it was shutting down. This week it announced that its assets, including the Bloodhound Supersonic Car (SSC), had been acquired by an enthusiastic – and wealthy – supporter.
“We are absolutely delighted that on Monday 17th December, the business and assets were bought, allowing the Project to continue,” the team said in a statement.
“The acquisition was made by Yorkshire-based entrepreneur Ian Warhurst. Ian is a mechanical engineer by training, with a strong background in managing a highly successful business in the automotive engineering sector, so he will bring a lot of expertise to the Project.”
Warhurst and his family, says the team, have been enthusiastic Bloodhound supporters for many years, and this inspired his new involvement with the Project.
“I am delighted to have been able to safeguard the business and assets preventing the project breakup,” he said. “I know how important it is to inspire young people about science, technology, engineering and maths, and I want to ensure Bloodhound can continue doing that into the future.
“It’s clear how much this unique British project means to people and I have been overwhelmed by the messages of thanks I have received in the last few days.”
The record attempt was due to be made late next year at Hakskeen Pan in the Kalahari Desert, where retired pilot Andy Green planned to beat the 1228km/h land-speed record he set in the United States in 1997. The target is for Bloodhound to become the first car to reach 1000mph (1610km/h). A track 19km long and 500 metres wide has been prepared, with members of the local community hired to clear 16 000 tons of rock and stone to smooth the surface.
The team said in its announcement this week: “Although it has been a frustrating few months for Bloodhound, we are thrilled that Ian has saved Bloodhound SSC from closure for the country and the many supporters around the world who have been inspired by the Project. We now have a lot of planning to do for 2019 and beyond.”
Motor Racing meets Machine Learning
The futuristic car technology of tomorrow is being built today in both racing cars and
toys, writes ARTHUR GOLDSTUCK
The car of tomorrow, most of us imagine, is being built by the great automobile manufacturers of the world. More and more, however, we are seeing information technology companies joining the race to power the autonomous vehicle future.
Last year, chip-maker Intel paid $15.3-billion to acquire Israeli company Mobileye, a leader in computer vision for autonomous driving technology. Google’s autonomous taxi division, Waymo, has been valued at $45-billion.
Now there’s a new name to add to the roster of technology giants driving the future.
Amazon Web Services, the world’s biggest cloud computing service and a subsidiary of Amazon.com, last month unveiled a scale model autonomous racing car for developers to build new artificial intelligence applications. Almost in the same breath, at its annual re:Invent conference in Las Vegas, it showcased the work being done with machine learning in Formula 1 racing.
AWS DeepRacer is a 1/18th scale fully autonomous race car, designed to incorporate the features and behaviour of a full-sized vehicle. It boasts all-wheel drive, monster truck tires, an HD video camera, and on-board computing power. In short, everything a kid would want of a self-driving toy car.
But then, it also adds everything a developer would need to make the car autonomous in ways that, for now, can only be imagined. It uses a new form of machine learning (ML), the technology that allows computer systems to improve their functions progressively as they receive feedback from their activities. ML is at the heart of artificial intelligence (AI), and will be core to autonomous, self-driving vehicles.
AWS has taken ML a step further, with an approach called reinforcement learning. This allows for quicker development of ML models and applications, and DeepRacer is designed to allow developers to experiment with and hone their skill in this area. It is built on top of another AWS platform, called Amazon SageMaker, which enables developers and data scientists to build, train, and deploy machine learning quickly and easily.
Along with DeepRacer, AWS also announced the DeepRacer League, the world’s first global autonomous racing league, open to anyone who orders the scale model from AWS.
As if to prove that DeepRacer is not just a quirky entry into the world of motor racing, AWS also showcased the work it is doing with the Formula One Group. Ross Brawn, Formula 1’s managing director of Motor Sports, joined AWS CEO Andy Jassy during the keynote address at the re:Invent conference, to demonstrate how motor racing meets machine learning.
“More than a million data points a second are transmitted between car and team during a Formula 1 race,” he said. “From this data, we can make predictions about what we expect to happen in a wheel-to-wheel situation, overtaking advantage, and pit stop advantage. ML can help us apply a proper analysis of a situation, and also bring it to fans.
“Formula 1 is a complete team contest. If you look at a video of tyre-changing in a pit stop – it takes 1.6 seconds to change four wheels and tyres – blink and you will miss it. Imagine the training that goes into it? It’s also a contest of innovative minds.”
Formula 1 racing has more than 500 million global fans and generated $1.8 billion in revenue in 2017. As a result, there are massive demands on performance, analysis and information.
During a race, up to 120 sensors on each car generate up to 3GB of data and 1 500 data points – every second. It is impossible to analyse this data on the fly without an ML platform like Amazon SageMaker. It has a further advantage: the data scientists are able to incorporate 65 years of historical race data to compare performance, make predictions, and provide insights into the teams’ and drivers’ split-second decisions and strategies.
This means Formula 1 can pinpoint how a driver is performing and whether or not drivers have pushed themselves over the limit.
“By leveraging Amazon SageMaker and AWS’s machine-learning services, we are able to deliver these powerful insights and predictions to fans in real time,” said Pete Samara, director of innovation and digital technology at Formula 1.