The new CLOi ServeBot has four doors and storage space to automate deliveries. | Source: LG Business Solutions

LG Business Solutions USA Inc. unveiled its latest LG CLOi ServeBot yesterday. Model LDLIM31 is an autonomous service robot that can provide safe deliveries in hospitality and healthcare settings, it said. 

Introduced at the HITEC 2024 hospitality technology trade show, the latest CLOi ServeBot features a four-door design. LG said that the robot has ample storage space and that it can performs simple and repetitive delivery tasks to reduce the burden on staffers.

“Our newest service robot brings a new level of functionality and flexibility to the hospitality and healthcare channels,” stated Mike Kosla, senior vice president of LG Business Solutions USA.

“Featuring advanced platform technologies that include AI, communications, and control, the new CLOi ServeBot is going to help our hospitality and healthcare customers streamline their operations,” he added. “The introduction of a door-type service robot reinforces our commitment to constantly innovate in ways that bring meaningful new benefits to our customers.”

The CLOi ServeBot is designed for hospitality and healthcare. LG Electronics

LG Electronics widens its portfolio of B2B robots

LG serves commercial customers in the U.S. lodging and hospitality, digital signage, systems integration, healthcare, education, government, and industrial markets. The Englewood Cliffs, N.J.-based company launched its CLOi CarryBot in the U.S. earlier this year. The autonomous mobile robot (AMR) can move up to 1.2 m/sec. (2.6 mph) with 18 hours of runtime and a six-hour charge time.

According to LG Electronics USA Business Solutions, a unit of Seoul-based LG Electronics Inc., this latest offering bolsters its portfolio of AI robots and robot control systems.

The new system also aligns with the company’s plan to accelerate the expansion of its business-to-business (B2B) offerings, particularly in delivery and logistics services. 

In March, LG Electronics led the $60 million Series C round for service robot maker Bear Robotics Inc.

CLOi ServeBot LDLIM31 designed for capacity, stability

LG’s new door-type robot has four internal compartments, each capable of holding items weighing up to 30 kg (66.14 lb.). These compartments allow it to make multiple deliveries or collections at a time.

The robot’s cargo space can accommodate as many as 32 standard-size, 12-oz. coffee cups, explained the company. Users can also adjust the shelving according to the item or load size. 

Tailored for indoor hospitality and healthcare environments, LG CLOi ServeBot can use elevators, expanding operational coverage. The robot has six wheels with independent suspension to provide stability. This enables the LDLIM31to transport beverages over uneven surfaces without significant spillage, said LG.

For user convenience, ServeBot’s doors can be set to open or close automatically during operation. Using built-in cameras in its internal compartments, the robot can detect when items have been removed and the delivery is completed. 

The robot is equipped with algorithms that allow it to safely navigate around obstacles, determine the optimal route to its destinations, and communicate with up to 20 other CLOi ServeBots to maximize task efficiency and avoid potential collisions. 

CLOi ServeBot also has a front-facing 10.1-in. (25.6 cm) display that serves as a mobile advertising platform. Users can upload content for display via the LG CLOi Cloud Station for mobile and web use or the CMS mobile app.

The door-type CLOi ServeBot has won the 2024 Red Dot “Best of the Best” design award and the 2024 iF Design Award.

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Hyundai’s DAL-e delivery robot is equipped with face identification AI developed by Robotics LAB. | Source: Hyundai Motor Group

South Korea, which already has the world’s highest robot density, is getting more service robots. Hyundai Motor Group last week announced the deployment of the DAL-e Delivery robot from Hyundai Motor Co. and Kia Corp., as well as Hyundai WIA’s Parking Robot.

The partners said the robots will deliver beverages and provide parking services, respectively, at Factorial Seongsu, a smart building owned by IGIS Asset Management.

“With DAL-e’s full-fledged delivery service, we aim to make Factorial Seongsu the first building to apply our Robot Total Solution,” stated Dong Jin Hyun, vice president and head of the Robotics LAB of Hyundai Motor and Kia. “We plan to expand our robotics services to more buildings, making these technological enhancements a major criterion for space innovation.”

Parking Robot moves cars, Dal-e delivers drinks

At the building, DAL-e Delivery will autonomously navigate to provide quick and efficient delivery services, said Hyundai Motor. It is equipped with AI face-identification technology developed by Robotics LAB that Hyundai claimed is 99.9% accurate. 

The autonomous Parking Robot can maneuver into tight spaces, increasing parking space utilization compared with human parking, the company said. Hyundai WIA has also developed a Smart Parking Control System that can manage up to 50 parking robots simultaneously. 

Hyundai already has plans to expand this deployment in the coming months. Starting in Q3, the Parking Robot will work alongside Hyundai Motor and Kia’s Automatic Charging Robot (ACR) to serve electric vehicles (EVs). 

Hyundai said it is working toward a proposed “Robot Total Solution” development plan. This plan involves using various robots and facial recognition systems in smart buildings, starting with Factorial Seongsu.

The company added that it hopes to develop an integrated control system for managing multiple delivery robots within the Robot Total Solution. 

Hyundai invests in other robotic ventures

In addition to its office robot deployment, Hyundai has been investing in other robotics ventures. In 2020, it acquired Boston Dynamics, which has been developing and commercializing the legged Spot and Atlas robots.

Last month, Aptiv PLC and Hyundai Motor Group completed their ownership restructuring transitions for Motional AD LLC. Earlier this year, Aptiv said it would stop funding Motional after incurring millions of dollars in losses.

Aptiv had forecast a non-cash equity loss of about $340 million in 2024. Aptiv has sold an 11% common equity interest in the autonomous vehicle developer to Hyundai for about $448 million of cash consideration.

The mobility software company also exchanged 21% of its common equity in Motional for a like number of Motional preferred shares. This news came just weeks after Hyundai announced a $475 million funding round for Motional. With the funding, these transactions have resulted in the reduction of Aptiv’s common equity interest in Motional from 50% to just 15%. 

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Organization: Slip Robotics
Country: U.S.
Website: www.sliprobotics.com
Year Founded: 2019
Number of Employees: 11-50
Innovation Class: Application & Market

Imagine you’re a truck driver finally arriving at your destination after hours of driving. Once you drop off your cargo, you know you have hours more to go before the end of your workday.

In between all this driving, you spend a significant amount of time simply waiting for your trailer to be unloaded and loaded again. While there are robots that can unload pallets or boxes individually, Slip Robotics has taken a different approach to the problem.

Instead of creating a robotic arm to pick items individually, the Atlanta-based company developed SlipBot, also known as an automated loading robot (ALR).

It’s a large, omnidirectional mobile robot that can carry up to eight full pallets and a total of 6 tons. Once the pallets are on the ALR, it autonomously drives into a trailer for transport to the next destination.

When it gets there, it drives off the truck and into the warehouse. Once the truck has been unloaded, the ALRs waiting in the wings can drive onto the trailer.

This can reduce driver wait time from 1.5 hours down to just five minutes, said Slip Robotics. The company also said it can load 20 pallets per minute without driving a forklift into a trailer.

Besides reducing wait times for divers, Slip claimed that its robots can load eight times as many trailers with the same number of operators. It can also reduce damage by 40% by reducing touches and impacts in material handling.

Finally, the company said its systems can improve worker safety. Twenty-five percent of industrial accidents involve a loading dock, noted Slip Robotics, and ALRs make it so operators never need to enter trailers to unload, load, or secure.

Register now.

Explore the RBR50 Robotics Innovation Awards 2024.

RBR50 Robotics Innovation Awards 2024

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Zebra’s portfolio includes FlexShelf robots for parts fulfillment. Source: Zebra Technologies

Only 1 in 6 manufacturers has a clear understanding of its own processes, according to a new study from Zebra Technologies Corp. The report also found that 61% of manufacturers expect artificial intelligence to drive growth by 2029, up from 41% in 2024.

Zebra said the surge in AI interest, along with 92% of survey respondents prioritizing digital transformation, demonstrates manufacturers’ intent to improve data management and use new technologies that enhance visibility and quality throughout production.

“Manufacturers struggle with using their data effectively, so they recognize they must adopt AI and other digital technology solutions to create an agile, efficient manufacturing environment,” stated Enrique Herrera, industry principal for manufacturing at Zebra Technologies. “Zebra helps manufacturers work with technology in new ways to automate and augment workflows to achieve a well-connected plant floor where people and technology collaborate at scale.”

Zebra commissioned Azure Knowledge Corp. to conduct 1,200 online surveys among C-suite executives and IT and OT (information and operational technology) leaders within various manufacturing sectors. They included automotive, electronics, food and beverage, pharmaceuticals, and medical devices. Respondents were surveyed in Asia, Europe, Latin America, and North America.

The fully connected factory is elusive

Although manufacturers said digital transformation is a strategic priority, achieving a fully connected factory remains elusive, noted Zebra Technologies. The company asserted that visibility is key to optimizing efficiency, productivity, and quality on the plant floor.

However, only 16% of manufacturing leaders globally reported they have real-time, work-in-progress (WIP) monitoring across the entire manufacturing process, reported the 2024 Manufacturing Vision Study.

While nearly six in 10 manufacturing leaders said they expect to increase visibility across production and throughout the supply chain by 2029, one-third said getting IT and OT to agree on where to invest is a key barrier to digital transformation.

In addition, 86% of manufacturing leaders acknowledged that they are struggling to keep up with the pace of technological innovation and to securely integrate devices, sensors, and technologies throughout their facilities and supply chain. Zebra claimed that enterprises can use its systems for higher levels of security and manageability, as well as new analytics to elevate business performance.

Technology can augment workforce efficiency

Manufacturers are shifting their growth strategies by integrating and augmenting workers with AI and other technologies over the next five years, found Zebra’s study. Nearly three-quarters (73%) said they plan to reskill labor for data and technology usage, and seven in 10 said they expect to augment workers with mobility-enabling technology.

Manufacturers are implementing tools including tablets (51%), mobile computers (55%), and workforce management software (56%). In addition, 61% of manufacturing leaders said they plan to deploy wearable mobile computers.

Across the C-suite, IT, and OT understand how labor initiatives must extend beyond improving worker efficiency and productivity with technology. Six in 10 leaders ranked ongoing development, retraining/upskilling, and career path development to attract future talent as high priorities for their organizations.

Automation advances to optimize quality

The quest for quality has intensified as manufacturers across segments must do more with fewer resources. According to Zebra and Azure’s survey, global manufacturers said today’s most significant quality management issues are real-time visibility (33%), keeping up with new standards and regulations (29%), integrating data (27%), and maintaining traceability (27%).

Technology implementation plans are addressing these challenges. Over the next five years, many executives said they plan to implement robotics (65%), machine vision (66%), radio frequency identification (RFID; 66%), and fixed industrial scanners (57%).

Most survey respondents agreed that these automation decisions are driven by factors including the need to provide the workforce with high-value tasks (70%), meet service-level agreements (SLAs; 69%), and add more flexibility to their plant floors (64%).

Zebra Technologies shares regional findings

• Asia-Pacific (APAC): While only 30% of manufacturing leaders said they use machine vision across the plant floor in APAC, 67% are implementing or planning to deploy this technology within the next five years.
• Europe, the Middle East, and Africa (EMEA): In Europe, reskilling labor to enhance data and technology usage skills was the top-ranked workforce strategy for manufacturing leaders to drive growth today (46%) and in five years (71%).
• Latin America (LATAM): While only 24% of manufacturing leaders rely on track and trace technology in LATAM, 74% are implementing or plan to implement the technology in the next five years.
• North America: In this region, 68% of manufacturing leaders ranked deploying workforce development programs as their most important labor initiative.

The Manufacturing Vision Study provided insights around digitalization and the connected factory. Source: Zebra Technologies

Zebra to discuss digital transformation

While digital transformation is a priority for manufacturers, achieving it is fraught with obstacles, including the cost and availability of labor, scaling technology solutions, and the convergence of IT and OT, according to Zebra Technologies. The Lincolnshire, Ill.-based company said visibility is the first step to such transformation.

Emerging technologies such as robotics and AI enable manufacturers to use data to identify, react, and prioritize problems and projects so they can deliver incremental efficiencies that yield the greatest benefits, Zebra said. The company said it provides systems to enable businesses to intelligently connect data, assets, and people.

Zebra added that its portfolio, which includes software, mobile robots, machine vision, automation, and digital decisioning, can help boost visibility, optimize quality, and augment workforces. It has more than 50 years of experience in scanning, track-and-trace, and mobile computing systems.

The company has more than 10,000 partners across over 100 countries, as well as 80% of the Fortune 500 as customers. Zebra is hosting a webinar today about how to overcome top challenges to digitalization and automation.

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Vecna offers warehouses robotic tuggers, lift trucks, and pallet jacks. Source: Vecna Robotics

WALTHAM, Mass. — Although investment in robotics dipped in the past year, suppliers with proven products and business models have been finding funding. Vecna Robotics today announced the close of its Series C round at $100 million, with $40 million in new funding including equity and debt. The financing nearly doubles the company valuation since its Series B round.

“Finalizing this capital raise, with the help of our existing investors and a new financing partner, is huge validation that we are on the right track,” stated Craig Malloy, CEO of Vecna Robotics. “With fresh capital secured, we have the balance sheet to help us drive growth with our existing customers through improved product performance and the release of new automation technology that will change the game for material handling in warehousing and distribution.”

Vecna Robotics said its autonomous mobile robots (AMRs), Pivotal orchestration software, and round-the-clock Command Center can help supply chains automate critical workflows and maximize throughput at scale. The company has tightened its focus to self-driving forklifts, pallet jacks, and tuggers to address widespread labor shortages.

Vecna and GEODIS to automate case picking

Over the past year, Vecna Robotics has combined cloud software updates and investments in its Pivotal Command Center to help customers such as GEODIS, FedEx, Caterpillar, and Shape. They have realized as much as 70% performance improvements in ground-to-ground warehouse workflows including case picking, packaging, and cross-docking, it said.

Vecna said the cash infusion will support the launch of platforms that will enable it to “provide more deployment flexibility and reach into new workflows that are in high demand, while being able to continue delivering operator cost savings from Day 1.”

“GEODIS has been working with Vecna Robotics on the development of a new, groundbreaking case-picking solution that nearly doubles performance,” said Andy Johnston, senior director of innovation at GEODIS. “We are counting on this recent cash infusion at the company to speed up development and launch of a complete, market-ready offering that can be deployed right away.”

Vecna tests in house to ensure reliability

The Robot Report recently visited Vecna Robotics headquarters to see its “bowling alley,” where it tests its AMRs around the clock. The company tests capabilities including the “handshake” between its robots and conveyors.

For instance, during a demonstration, Vecna tested its Co-bot Pallet Jack (CPJ) picking up and dropping off heavy loads beyond what customers typically need. It tracks runtimes and multiple maneuvers, and a staffer stays overnight mainly to swap batteries.

“We’re always pleasantly surprised at our low failure rates,” observed Mark Fox, director of validation at Vecna. “We can replicate the conditions of a typical customer site, including obstacles. We analyze the scene and look at multiple pickups and drop offs so that performance doesn’t drop.”

Vecna has also developed sensing at height, enabled robots to accept some variance from existing maps, and participated in the MassRobotics interoperability standards effort.

“We’re working on applying our technology and data to case picking in addition to pallet movement,” explained test engineer Chinonso Ovuegbe.

What products and sectors are seeing the most demand?

“Self-driving forklifts and tuggers are our most popular products,” replied Fox. “Robotics-as-a-service [RaaS] per month is also popular, but some customers buy our products outright. Third-party logistics providers [3PLs] and automotive are booming.”

Investment and new COO to enable growth

Tiger Global Management, Proficio Capital Partners, and IMPULSE participated in Vecna Robotics’ Series C round. The company said the funding will allow it to deliver rapid returns on investment (ROI) to cost-conscious warehouse operators served by the $165 billion pallet-moving autonomy market.

To support its rapid expansion, Vecna also announced the appointment of Michael Helmbrecht as chief operating officer. He will oversee operations, manufacturing, IT, product, and customer success to ensure that the company continues to meet its customer-defined performance guarantees.

Helmbrecht has nearly 20 years of operations, product, and partnership experience from executive roles at Dell, Lifesize, and Ring Central. He joins Vecna after a year of triple-digit revenue growth, an over 100% increase in deployments, and the announcement of an industry-leading performance guarantee.

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As shown at CVPR, Omniverse Cloud Sensor RTX microservices generate high-fidelity sensor simulation from
an autonomous vehicle (left) and an autonomous mobile robot (right). Sources: NVIDIA, Fraunhofer IML (right)

NVIDIA Corp. today announced NVIDIA Omniverse Cloud Sensor RTX, a set of microservices that enable physically accurate sensor simulation to accelerate the development of all kinds of autonomous machines.

NVIDIA researchers are also presenting 50 research projects around visual generative AI at the Computer Vision and Pattern Recognition, or CVPR, conference this week in Seattle. They include new techniques to create and interpret images, videos, and 3D environments. In addition, the company said it has created its largest indoor synthetic dataset with Omniverse for CVPR’s AI City Challenge.

Sensors provide industrial manipulators, mobile robots, autonomous vehicles, humanoids, and smart spaces with the data they need to comprehend the physical world and make informed decisions.

NVIDIA said developers can use Omniverse Cloud Sensor RTX to test sensor perception and associated AI software in physically accurate, realistic virtual environments before real-world deployment. This can enhance safety while saving time and costs, it said.

“Developing safe and reliable autonomous machines powered by generative physical AI requires training and testing in physically based virtual worlds,” stated Rev Lebaredian, vice president of Omniverse and simulation technology at NVIDIA. “Omniverse Cloud Sensor RTX microservices will enable developers to easily build large-scale digital twins of factories, cities and even Earth — helping accelerate the next wave of AI.”

Omniverse Cloud Sensor RTX supports simulation at scale

Built on the OpenUSD framework and powered by NVIDIA RTX ray-tracing and neural-rendering technologies, Omniverse Cloud Sensor RTX combines real-world data from videos, cameras, radar, and lidar with synthetic data.

Omniverse Cloud Sensor RTX includes software application programming interfaces (APIs) to accelerate the development of autonomous machines for any industry, NVIDIA said.

Even for scenarios with limited real-world data, the microservices can simulate a broad range of activities, claimed the company. It cited examples such as whether a robotic arm is operating correctly, an airport luggage carousel is functional, a tree branch is blocking a roadway, a factory conveyor belt is in motion, or a robot or person is nearby.

Microservice to be available for AV development 

CARLA, Foretellix, and MathWorks are among the first software developers with access to Omniverse Cloud Sensor RTX for autonomous vehicles (AVs). The microservices will also enable sensor makers to validate and integrate digital twins of their systems in virtual environments, reducing the time needed for physical prototyping, said NVIDIA.

Omniverse Cloud Sensor RTX will be generally available later this year. NVIDIA noted that its announcement coincided with its first-place win at the Autonomous Grand Challenge for End-to-End Driving at Scale at CVPR.

The NVIDIA researchers’ winning workflow can be replicated in high-fidelity simulated environments with Omniverse Cloud Sensor RTX. Developers can use it to test self-driving scenarios in physically accurate environments before deploying AVs in the real world, said the company.

Two of NVIDIA’s papers — one on the training dynamics of diffusion models and another on high-definition maps for autonomous vehicles — are finalists for the Best Paper Awards at CVPR.

The company also said its win for the End-to-End Driving at Scale track demonstrates its use of generative AI for comprehensive self-driving models. The winning submission outperformed more than 450 entries worldwide and received CVPR’s Innovation Award.

Collectively, the work introduces artificial intelligence models that could accelerate the training of robots for manufacturing, enable artists to more quickly realize their visions, and help healthcare workers process radiology reports.

“Artificial intelligence — and generative AI in particular — represents a pivotal technological advancement,” said Jan Kautz, vice president of learning and perception research at NVIDIA. “At CVPR, NVIDIA Research is sharing how we’re pushing the boundaries of what’s possible — from powerful image-generation models that could supercharge professional creators to autonomous driving software that could help enable next-generation self-driving cars.”

Foundation model eases object pose estimation

NVIDIA researchers at CVPR are also presenting FoundationPose, a foundation model for object pose estimation and tracking that can be instantly applied to new objects during inference, without the need for fine tuning. The model uses either a small set of reference images or a 3D representation of an object to understand its shape. It set a new record on a benchmark for object pose estimation.

FoundationPose can then identify and track how that object moves and rotates in 3D across a video, even in poor lighting conditions or complex scenes with visual obstructions, explained NVIDIA.

Industrial robots could use FoundationPose to identify and track the objects they interact with. Augmented reality (AR) applications could also use it with AI to overlay visuals on a live scene.

NeRFDeformer transforms data from a single image

NVIDIA’s research includes a text-to-image model that can be customized to depict a specific object or character, a new model for object-pose estimation, a technique to edit neural radiance fields (NeRFs), and a visual language model that can understand memes. Additional papers introduce domain-specific innovations for industries including automotive, healthcare, and robotics.

A NeRF is an AI model that can render a 3D scene based on a series of 2D images taken from different positions in the environment. In robotics, NeRFs can generate immersive 3D renders of complex real-world scenes, such as a cluttered room or a construction site.

However, to make any changes, developers would need to manually define how the scene has transformed — or remake the NeRF entirely.

Researchers from the University of Illinois Urbana-Champaign and NVIDIA have simplified the process with NeRFDeformer. The method can transform an existing NeRF using a single RGB-D image, which is a combination of a normal photo and a depth map that captures how far each object in a scene is from the camera.

Researchers have simplified the process of generating a 3D scene from 2D images using NeRFs. Source: NVIDIA

JeDi model shows how to simplify image creation at CVPR

Creators typically use diffusion models to generate specific images based on text prompts. Prior research focused on the user training a model on a custom dataset, but the fine-tuning process can be time-consuming and inaccessible to general users, said NVIDIA.

JeDi, a paper by researchers from Johns Hopkins University, Toyota Technological Institute at Chicago, and NVIDIA, proposes a new technique that allows users to personalize the output of a diffusion model within a couple of seconds using reference images. The team found that the model outperforms existing methods.

NVIDIA added that JeDi can be combined with retrieval-augmented generation, or RAG, to generate visuals specific to a database, such as a brand’s product catalog.

JeDi is a new technique that allows users to easily personalize the output of a diffusion model within a couple of seconds using reference images, like an astronaut cat that can be placed in different environments. Source: NVIDIA

Visual language model helps AI get the picture

NVIDIA said it has collaborated with the Massachusetts Institute of Technology (MIT) to advance the state of the art for vision language models, which are generative AI models that can process videos, images, and text. The partners developed VILA, a family of open-source visual language models that they said outperforms prior neural networks on benchmarks that test how well AI models answer questions about images.

VILA’s pretraining process provided enhanced world knowledge, stronger in-context learning, and the ability to reason across multiple images, claimed the MIT and NVIDIA team.

The VILA model family can be optimized for inference using the NVIDIA TensorRT-LLM open-source library and can be deployed on NVIDIA GPUs in data centers, workstations, and edge devices.

VILA can understand memes and reason based on multiple images or video frames. Source: NVIDIA

Generative AI drives AV, smart city research at CVPR

NVIDIA Research has hundreds of scientists and engineers worldwide, with teams focused on topics including AI, computer graphics, computer vision, self-driving cars, and robotics. A dozen of the NVIDIA-authored CVPR papers focus on autonomous vehicle research.

“Producing and Leveraging Online Map Uncertainty in Trajectory Prediction,” a paper authored by researchers from the University of Toronto and NVIDIA, has been selected as one of 24 finalists for CVPR’s best paper award.

In addition, Sanja Fidler, vice president of AI research at NVIDIA, will present on vision language models at the Workshop on Autonomous Driving today.

NVIDIA has contributed to the CVPR AI City Challenge for the eighth consecutive year to help advance research and development for smart cities and industrial automation. The challenge’s datasets were generated using NVIDIA Omniverse, a platform of APIs, software development kits (SDKs), and services for building applications and workflows based on Universal Scene Description (OpenUSD).

AI City Challenge synthetic datasets span multiple environments generated by NVIDIA Omniverse, allowing hundreds of teams to test AI models in physical settings such as retail and warehouse environments to enhance operational efficiency. Source: NVIDIA

About the author

Isha Salian writes about deep learning, science and healthcare, among other topics, as part of NVIDIA’s corporate communications team. She first joined the company as an intern in summer 2015. Isha has a journalism M.A., as well as undergraduate degrees in communication and English, from Stanford.

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The Pik’r ball-picking robot at the 2024 U.S. Open at Pinehurst. Source: Korechi Innovations

While the 124th U.S. Open is all about human talent, skill, and composure under competitive pressure, robots are finding their place. As golfers practice their drives on the newly converted Cradle 9-hole course at Pinehurst Resort, the new Pick’r robot from Korechi Innovations Inc. is safely and efficiently retrieving balls.

Korechi said the Pick’r-1500 is designed for rugged terrain. It features a durable steel frame and a thick stainless-steel shell to ensure operations in the harsh conditions of a professional practice range.

The Pick’r-1500 includes advanced GPS technology and can collect thousands of golf balls daily, providing a constant supply for players, said the Oshawa, Ontario-based company.

Pik‘r promises efficiency and sustainability

Korechi Innovations said it introduced the Pik‘r-1500 at the U.S. Open to highlight its capacity and reliability. The robot‘s lightweight design, paired with a long-lasting battery, allows for all-day operation, minimizing disruptions to practice sessions, according to the company.

Not only can the autonomous ball retriever reduce the need for workers to recover balls, but it can also significantly cut down on operational costs and environmental impact, operating on less than $1 of electricity per day, said Korechi. As golf facilities worldwide face staffing shortages, the Pik‘r offers a sustainable solution to the labor-intensive task of range picking.

By automating ball retrieval, staff can focus on enhancing guest experiences and other value-added services. This shift also aligns with the growing trend towards sustainable practices in sports management, Korechi said.

About Korechi Innovations

Korechi Innovations designs and manufactures autonomous robots for agricultural and sports applications. Since its entry into the golf industry in 2019, the company said it has deployed Pik‘r across North America, retrieving millions of balls at major golf facilities.

As the U.S. Open continues in North Carolina, Korechi said it is demonstrating to golf industry professionals and enthusiasts the future of golf range management through the the Pik‘r-1500’s performance and reliability.

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Collaborative Robotics has kept its actual robot out of public view. | Source: Adobe Stock, Photoshopped by The Robot Report

Collaborative Robotics, a developer of cobots for logistics, today announced the establishment of a Foundation Models AI team. Michael Vogelsong, a founder of Amazon’s Deep Learning Tech team, will lead the new team in Seattle.

“Our cobots are already doing meaningful work in production on behalf of our customers,” stated Brad Porter, CEO of Collaborative Robotics. “Our investment in building a dedicated foundation models AI team for robotics represents a significant step forward as we continue to increase the collaborative potential of our cobots.”

“The foundation models AI team will explore the cutting-edge possibilities of AI in enhancing robotic capabilities, particularly in the area of bimanual manipulation and low-latency multimodal models,” he added. “We aim to achieve a new level of comprehension and control in our robots, enabling them to understand and respond effectively to complex tasks and environments. I am looking forward to seeing the innovations this talented team creates.”

Collaborative Robotics keeps its system under wraps

In April, Collaborative Robotics closed its $100 million Series B round toward commercializing its autonomous mobile manipulator. The company has been very secretive about the actual design of its system, releasing only scant details about the payload capabilities and the fact that is a wheeled collaborative robot.

At the time, Porter told The Robot Report that the new cobot’s base is capable of omnidirectional motion with four wheels and a swerve-drive design, along with a central tower-like structure that can acquire, carry, and place totes and boxes around a warehouse.

Brad Porter of Collaborative Robotics (far right) participated in a debate on whether humanoid robots are reality or hype at Robotics Invest this week in Boston. Credit: Eugene Demaitre

Foundation AI models coming to robotics

Foundation AI models are currently one of the hottest topics in robotics, with many companies investing in both talent and intellectual property to develop the technology. Foundation models offer the promise of generalizing behaviors and reducing the effort to build and maintain special-purpose models.

Collaborative Robotics said its new Foundation Models AI team will concentrate on integrating advanced machine-learning techniques into its production robots. By combining existing foundation models, novel research, and strategic partnerships with the practical experience from running systems live in production environments, the team aims to improve the adaptability and precision of robotic tasks.

Building on the company’s earlier work in developing an Auditable Control and Planning Framework (ACoP), this research will explore how models that process text, vision, and actions can interact and create a real-time feedback loop for adaptive control.

The company also announced a that it is funding Ph.D. work at the University of Washington through a “significant” gift. This gift will sponsor the research of Prof. Sidd Srinivasa, an academic leader in AI and robotics, who also serves as an advisor to Collaborative Robotics.

“The collaboration with Cobot supports our ongoing research at the University of Washington,” said Srinivasa. “Cobot’s commitment to advancing AI and robotics aligns well with our research goals and will help us advance robotic capabilities across multiple dimensions and particularly in the area of bimanual manipulation. ”

Collaborative Robotics plans this month to open its Seattle office, which will serve as a hub for these advanced research activities. The company said it expects the city’s tech ecosystem to support its expansion and research goals.

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Organization: Instock Inc.
Country: U.S.
Website: instock.com
Year Founded: 2020
Number of Employees: 11-50
Innovation Class: Technology

Instock came onto The Robot Report‘s radar when it became part of the Amazon Industrial Fund’s portfolio of robotics investments. This is the same fund that invested in Agility Robotics and many other notable companies.

Instock is taking a unique and flexible approach to automated storage and retrieval systems (ASRS). Most of these systems involve complex racking that moves bins around and places them onto autonomous mobile robots (AMRs) that bring those bins to picking robots or human pickers.

Instock doesn’t take this approach. Instead, the only moving part within the system is the AMRs, which pick up the bins themselves by gripping the bin wings and bringing them to workstations.

To travel between levels and maximize space, Instock’s AMRs drive along curved ramps placed at the end of the company’s modular racks. The AMRs then use magnets to drive upside down along the ceiling of the rack. When on the ceiling, the robot places itself above a bin and grabs from the top with its unique gripper.

The AMRs can then use the ramps to travel to whatever level they need to be at to deliver the bin to picking stations. The suspended mobile robots use the same system to bring bins back to the racks.

Because the only moving part within the entire system is the AMRs, Instock said its ASRS is easy to fix when things go wrong. Similar systems might require the entire ASRS to be shut down while repairs are made to one module, but with Instock, users simply need to remove the malfunctioning robot for maintenance.

Instock also claimed that its ASRS could require less maintenance than traditional systems.

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Floware includes AMRs, fleet management software, real-time performance dashboards and more. | Credit: Floatic

Korea-based Floatic, a warehouse robotic solutions provider, raised $3.8 million in a pre-Series A bridge round. The investment was led by Capstone Partners and included Quantum Ventures Korea, Bluepoint, BNK Venture Investment, and BSK Investment.

Floatic has raised a total of $8 million since it was founded in 2021. Floatic attracted seed investments from South Korean tech giant Naver Corp.’s D2SF and Kakao Corp.’s Kakao Ventures shortly after it was founded. It then closed a $2.5 million pre-Series A round in 2022.

The company plans to use the funding to extend its research and development efforts and enhance its product as it prepares for commercialization this year.

Floatic develops and offers Floware, a robotic system for e-commerce picking. It offers a complete solution from integration to deployment and operation in less than six weeks, with minimum infrastructure and financial requirements, according to the company. Floatic claims its approach increases productivity up to 3.5 times compared to manual picking.

Floware consists of autonomous mobile robots (AMR) designed specifically for warehouses and a management platform tailored to optimizing warehouse workflow. The solution includes features such as the ‘Picking Guide’ and a modular software algorithm that enables flexible operation and real-time management.

“Warehouses have diverse variables daily, making it difficult to provide the necessary solutions without a proper understanding of the site,” said Chan Lee, CEO of Floatic. “We have been focusing on the user voices and developed the product based on this from the very beginning, which makes a crucial difference in the solution.”

The company has been conducting on-site field tests with 3PL companies and local warehouses, and collaborating with leading logistics partners in Korea such as POSCO DX and LogisALL. It intends to make a full commercialization in the second half of this year.

“We will continue to invest in developing and creating the feasible robotic solutions needed to establish the most efficient warehouse environment, thoroughly focusing on the market from a user-centric perspective,” Lee added. “This fundraising will be a powerful engine to achieve this goal, and we are grateful to our investors for supporting us.”

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Aramark is deploying the CC3 autonomous floor scrubber at the Kay Bailey Hutchison Convention Center in Texas. | Source: Aramark

With the average commercial building spanning around 17,200 square feet, companies could be spending up to 350 hours each month on cleaning tasks, according to data from Commercial Cleaning Corp. This is a significant amount of time and money that businesses could be putting towards more value returning efforts. Aramark is hoping to improve efficiency and achieve superior cleaning results by deploying Pringle Robotics’ autonomous cleaning robots. 

Aramark is a global provider of food and facilities services, with operations spanning the education, healthcare, business and industry, sports, leisure, and corrections industries. As part of its partnership with Pringle Robotics, Aramark will install the company’s floor-cleaning robots and operation software systems at key customer locations. 

“Our clients depend on us to introduce leading technologies that can help to manage their facilities in a way that delivers superior cleaning efficacy with an attractive cost structure,” John Hanner, president and CEO of Aramark Facilities Management, said.

Edwards, Ill.-based Pringle Robotics develops robots for facilities management. The company has a line of 13 different robots, which include cleaning robots and service robots. Its robots work in airports, casinos, gyms, hospitals, hotels, malls, office buildings, restaurants, assisted living facilities, schools, museums, and more. In particular, Aramark is using Pringle Robotics’ CC1 and CC3 autonomous floor-cleaning robots. 

Inside Pringle’s deployment with Aramark

Pringle Robotics says it worked closely with Aramark to evaluate, pilot, and deploy the robots and customized and integrated software systems as Aramark accounts across its portfolio. 

CC1 is a multipurpose autonomous commercial floor-cleaning robot. It has four cleaning modes, including sweep, mop, scrub, and vacuum modes. For additional flexibility, it also includes manual control for spot treatment. CC3, on the other hand, is an industrial-grade autonomous floor scrubber. It can handle hard floors indoors and outdoors and can cover 20,000 square feet per hour. Both robots include an automatic charging and water dumping/refilling station.

One of the facilities where the robots are at work is Aramark’s Kay Bailey Hutchinson Convention Center Dallas (KBHCCD). This convention center is one of the largest in the country, and it serves over a million visitors every year. At KBHCCD, the autonomous robots navigate through the convention center, cleaning and scrubbing a variety of floor types, including hard surfaces, carpeted meeting rooms, and lobbies. 

“The successful deployment of our floor cleaning robots and facility management software integrations at Aramark’s customer facilities points the way towards optimized and scalable cleaning innovation,” said Sudheer Sajja, founder and CEO of Pringle Robotics.

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Organization: Opteran
Country: U.K.
Website: https://opteran.com
Year Founded: 2019
Number of Employees: 11-50
Innovation Class: Technology

Current approaches to machine autonomy require a lot of sensor data and expensive compute and often still fail when exposed to the dynamic nature of the real world, according to Opteran. The company earned RBR50 recognition in 2021 for its lightweight Opteran Development kit, which took inspiration from research into insect intelligence.

In December 2023, Opteran commercialized its vision-based approach to autonomy by releasing Opteran Mind. The company, which has a presence in the U.K., Japan, and the U.S., announced that its new algorithms don’t require training, extensive infrastructure, or connectivity for perception and navigation.

This is an alternative to other AI and simultaneous localization and mapping (SLAM), which are based on decades-old models of the human visual cortex, said James Marshall, a professor at the University of Sheffield and chief scientific officer at Opteran. Animal brains evolved to solve for motion first, not points in space, he noted.

Instead, Opteran Mind is a software product that can run with low-cost, 2D CMOS cameras and on low-power compute for non-deterministic path planning. OEMs and systems integrators can build bespoke systems on the reference hardware for mobile robots, aerial drones, and other devices.

“We provide localization, mapping, and collision prediction from robust panoramic, stabilized 3D CMOS camera input,” explained Marshall.

At a recent live demonstration at MassRobotics in Boston, the company showed how a simple autonomous mobile robot (AMR) using Opteran Mind 4.1 could navigate and avoid obstacles in a mirrored course that would normally be difficult for other technologies.

It is currently focusing on automated guided vehicles (AGVs), AMRs, and drones for warehousing, inspection, and maintenance.

“We have the only solution that provides robust localization in challenging environments with scene changes, aliasing, and highly dynamic light using the lowest-cost cameras and compute,” it said.

The company is currently working toward safety certifications and “decision engines,” according to Marshall.

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Three-fourths of store managers say Tally improves productivity for their teams. | Credit: Simbe Robotics

Simbe Robotics Inc. deployed its first Tally autonomous mobile robot to collect front-of-house retail inventory in 2015. Since that launch, the company has developed the system to track inventory levels in near real-time for retail store managers.

The Tally mobile robot autonomously traverses the store aisles and uses onboard cameras to image all store shelves. These images are then processed to extract item SKUs and inventory counts, which are then summarized in the inventory console for use by the store management team.

Simbe has successfully deployed Tally at companies such as SpartanNash and Wakefern. The South San Francisco-based company is also a 2024 RBR50 award winner for its expansive deployment at BJ’s Wholesale Club.

No more manual counting

Without Tally, inventory counting is a manual process, noted Simbe Robotics. Store clerks restock front-of-house inventory, and the process of counting it is also a part of this job function.

The advent of grocery e-commerce and online order fulfillment has complicated the inventory management task. Fulfillment times are extended when there is not enough inventory on the shelves to support both in-store customers and online orders. This often leads to chaos on the floor for workers who have to react and scramble to pull inventory from the warehouse to keep store shelves stocked.

According to Simbe, Tally can cut fulfillment times in half. It does that in a few ways. The mobile robot can provide an optimal path for selecting items to fulfill an online order, cutting back on the time an associate is traversing the store.

In addition, Tally an help with catalog accuracy so the team can see what’s in stock and doesn’t end up wasting time scanning a shelf only to find out that it’s out of stock.

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Simbe Robotics shares survey data

Recently, Simbe unveiled data from its first annual “Store Team Technology Sentiment Report.” The company polled its current installed base to get detailed insights about their use of Tally and how effective the robot is for store managers.

One of the primary results from the study shows that 90% of store managers said that Tally makes their jobs easier. Top of mind for store managers is customer service and satisfaction.

By automating monotonous tasks, the survey found that Tally can save teammates up to 50 hours each week – and three out of four store managers said they can better support shoppers as a result.

Also of importance to store managers is increasing store team retention, operational excellence, and cost discipline. The quit rate for retail workers is more than 70% higher than other U.S. industries. Labor turnover in retail has reached 95% in recent years – in part due to a lack of proper tools for tasks like inventory management, which associates consistently cite as the worst store team responsibility.

The report is based on an online survey of 174 store managers at U.S.-based retailers that Simbe conducted from April 1 to 20, 2024. The store managers surveyed have been using Tally for six months or more. The company said the results have a margin of error of +/-7% at a 95% confidence level.

Tally can improve staff retention

The survey showed that Tally can help improve store team retention, said Simbe Robotics. The majority of team members said they feel more fulfilled by their work since Tally arrived. Since fulfillment is a key driver of employee retention, this is especially important as retailers face some of the worst labor shortages in history.

When store managers have current inventory data, they can make informed decisions about prioritizing restocking tasks. Nine out of 10 store managers said Tally makes their jobs easier.

For instance, the robot’s pick path optimization lets store teams quickly and easily find items for online orders. This can cut order-fulfillment times in half, according to Simbe.

“As a former retail store manager, I experienced firsthand the inefficiencies of manually managing inventory and its impact on business operations and team morale,” said Jeremy Wortsman, senior director of customer success at Simbe.

“We’re pleased that this inaugural survey so fully quantifies the impact of our technology on operational excellence in retail, as well as store teams’ daily experience and overall fulfillment in their roles,” he said. “Only Simbe’s customers have produced such results at scale for years, and as we deploy Tally to thousands of new stores in response to increasing demand, we’re committed to keeping a pulse on store team sentiment.”

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The Cobalt mobile robot features autonomous driving technology, allowing it to navigate through various terrains and obstacles with ease, ensuring constant vigilance without human operation. | Credit: Cobalt robotics

Cobalt Robotics has been acquired by investor Dean Drako, and the name of the firm has been changed to Cobalt AI. Financial terms of the acquisition were not disclosed. The name change was made to more accurately represent the future direction of the company and the products it offers.

Drako is the founder and CEO of Eagle Eye Networks, in addition to a number of other enterprises and side projects. Cobalt AI fits closest to the Eagle Eye Smart Video Surveillance portfolio of solutions.

There are no major changes to Cobalt’s leadership other than Drako serving as the company’s chairman. Ken Wolff, Cobalt’s current CEO, will continue leading the company. The company will also continue to operate as an independent company with its current management team and entire staff.

Cobalt started with mobile robotics

Cobalt Robotics was founded in 2016 as a developer of autonomous mobile robots (AMRs) for security applications. The AMRs were designed to patrol the interior of a facility while actively surveilling activities and remotely monitoring the facilities as an extension of the building’s security.

To meet the growing needs of its corporate customers, Cobalt developed AI-based algorithms for alarm filtering, remote monitoring, sensing, and other autonomous data-gathering functions. In addition to the sensors onboard the Cobalt AMR, the Cobalt Monitoring Intelligence and Cobalt Command Center gather data from a broad range of cameras, access control systems, robots, and other edge devices.

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“The company monitoring and command center technology is a catalyst for a new era of security,” said Drako. “They have created field-proven AI to make security and guarding tremendously more effective and efficient. Furthermore, Cobalt’s open platform strategy, which integrates with a plethora of video and access systems, is aligned with the open product strategy I believe in.”

Drako’s vision for sensor-monitoring AI

In a recent LinkedIn post, Drako explained why he made the deal.

“I did an extensive search, with a goal to acquire the company with the most powerful AI-based enterprise security automation technology in our physical security industry. Cobalt’s AI technologies, including their monitoring and command center solutions, are years ahead — they will be one of the catalysts for a new era of security.

“Importantly, Cobalt’s open platform strategy, which integrates with a wide range of video and access control systems, aligns with the open product strategy I strongly believe in.

“I am working closely with Cobalt AI’s leadership team, as well as infusing significant capital, to quickly scale their ‘human verified AI’ technology across enterprise security applications.”

Cobalt AI is marketing “Human verified AI” to promote human-in-the loop methods of leveraging AI and human-based perception to monitor and interpret security information. | Credit: Dean Drako

“We are thrilled that Dean Drako has acquired Cobalt and will serve as chairman. Dean has invested capital and strategic insights to grow other physical security companies to unicorns and technology leaders in their space,” said Wolff. “We share a mutual vision of the tremendous advantages of automation through AI with human verification.  Drako’s acquisition validates our strategy to improve monitoring, response times and lower costs and also gives us the capital to deliver for our enterprise clients.”

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Serve has partnerships with Uber Eats, 7-Eleven, NVIDIA, and Delivery Hero, plus DriveU.auto. | Source: Serve Robotics

Serve Robotics Inc. is teaming up with DriveU.auto to deploy the company’s connectivity platform into Serve’s commercially deployed robotic fleet. The platform will enhance its ability to monitor its autonomous delivery robots remotely, said Serve Robotics. 

DriveU.auto’s platform will add to the suite of tools that the delivery robot company is using as it deploys up to 2,000 systems on the Uber Eats platform. 

“In order to rapidly scale to thousands of robots, Serve needs to leverage the capabilities of world-class technology partners like DriveU.auto,” stated Dmitry Demeshchuk, co-founder and vice president of software engineering at Serve. “DriveU’s connectivity platform will help us improve the resilience and performance of our fleet, unlock operational efficiencies, and realize economies of scale as we pursue mass-market autonomous delivery.”

DriveU.auto has developed and deployed a software-based connectivity platform for the teleoperation of robots and autonomous vehicles. The Tel Aviv, Israel-based company claimed that its system enables remote driving (direct drive) or high-level commands (remote assistance) at very low latency and high reliability.

DriveU.auto’s system is based on its proprietary cellular bonding and dynamic video encoding technologies. It said its customers and partners include autonomous vehicle developers, including cars, trucks, and shuttles, makers of delivery robots, OEMs, and Tier 1 automotive suppliers. They have used the company’s platform on the roads in the EU, U.S., China, Japan, and Israel.

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Why Serve picked the DriveU.auto platform

Serve said it evaluated DriveU.auto alongside other competitive offerings. It landed on DriveU.auto’s platform because of its reliable, low latent, and uninterrupted connectivity. The company says this allows robots to share real-time telematics, access cloud computing, and enable remote supervision in edge cases. 

“We are thankful for the opportunity to engage as a trusted partner with Serve Robotics,” Alon Podhurst, CEO of DriveU.auto, said. “DriveU.auto is committed to enabling the large-scale rollout of driverless fleets safely and efficiently. Connectivity is a critical element in every driverless vehicle. Our expanding roster of commercial partnerships is a testament to DriveU’s leading position in enabling AV operations.

DriveU.auto also provides native support of the NVIDIA Jetson platform, which provides hardware-accelerated video encoding and decoding, reduces network bandwidth and latency, and results in better video quality. This was an added value for Serve. 

In April of this year, Redwood City, Calif-based Serve Robotics went public on the Nasdaq Stock Market under the symbol “SERV.” The company said it expected its initial public offering of 10 million shares of common stock to generate $40 million in gross proceeds, before underwriting discounts and offering expenses. 

Serve Robotics builds and maintains its fleet of robots for customers as a robotics-as-a-service (RaaS) business. In 2021, Serve spun out of Uber, and it has maintained an operating contract with Uber Eats for local delivery in select locations.  Other big customers have included Walmart and 7-Eleven.

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