In the post-COVID era, new and established companies are seeking business efficiencies, as well as labor support, driving market demand for automation. Cartken Inc. has deployed robots for a handful of customer applications, including Starbucks and Grubhub deliveries.
Cartken CEO Chris Bersch said that he and co-founders Jonas Witt, Jake Stelman, and Anjali Jindal Naik got excited about the prospect for robots because of the technology’s readiness and affordability. The four Google alumni decided the timing was right and founded the Oakland, Calif.-based company in 2019.
“What we saw was a technological inflection point where we could make small, self-driving vehicles work on the street,” said Bersch. “Because it doesn’t make sense to build a $20,000 robot that can deliver burritos.”
Revenue from robotic last-mile deliveries is expected to grow more than ninefold to $670 million in 2030, up from $70 million in 2022, according to ABI Research.
Jetson helps deliver RaaS
Cartken is among several autonomous mobile robot (AMR) startups using NVIDIA Jetson to make advances across agriculture, manufacturing, retail, and last-mile delivery. The company offers robotics as a service (RaaS) to customers in a pay-for-usage model.
As a white-label technology provider, Cartken enables companies to customize the robots for their particular brand appearance and specific application features. A growing number of companies is offering RaaS for everything from on-demand remote museum visits to autonomous industrial lawn mowers, noted NVIDIA.
Cartken relies on the NVIDIA Jetson AGX Orin, which can handle multiple sensors and cameras. The Jetson embedded computing modules run six cameras that aid in mapping and navigation, as well as wheel odometry to measure how far a robot has moved.
“Cartken chose the Jetson edge AI platform because it offers superior embedded computational performance, which is needed to run Cartken's advanced AI algorithms,” said Bersch. “In addition, the low energy consumption allows Cartken's robots to run a whole day on a single battery charge.”
Cartken’s robots use Jetson to run simultaneous localization and mapping, or SLAM, to automatically build maps of their surroundings for navigation.
“They are basically Level 4 autonomy—it’s based on visual processing, so we can map out a whole area,” Bersch said. “The nice thing about our navigation is that it works both indoors and outdoors, so GPS is optional—we can localize based on purely visual features.”
In addition, Cartken is a member of NVIDIA Inception, a program to help startups with GPU technologies, software, and business development.
Cartken uses NVIDIA Jetson for sensing and navigation. Source: NVIDIA
Cartken delivery robots roll out to campuses
Cartken’s robots are serving Grubhub deliveries at the University of Arizona and Ohio State. Grubhub users can order on the app as they normally would and get a tracking link to follow their order’s progress. Customers are informed that their deliveries will be by a robot, and they can use the app to unlock the robot’s lid to grab grub and go.
Some might wonder if the delivery fee for such entertaining delivery technology is the same. “I believe it’s the same, but you don’t have to tip,” Bersch said.
Mitsubishi Electric is a distributor for Cartken in Japan. It has deployed Cartken’s robots in AEON Malls in Tokoname and Toki to deliver Starbucks coffee and food. The companies are also testing a “smart city” concept for outdoor deliveries of Starbucks goods within the neighboring parks, apartments, and homes.
In addition, Mitsubishi, Cartken, and others are working on deliveries inside a multilevel office building.
Looking ahead, Cartken’s CEO says the next big challenge is scaling up robot manufacturing to keep pace with orders. It has strong demand from partners, including Grubhub, Mitsubishi, and U.K. delivery company DPD.
In September, Cartken announced a partnership with Magna International, a leading global automotive supplier, to help scale up manufacturing of its robots. The agreement offers production of thousands of AMRs as well as development of additional robot models for different use cases.
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