XBOTS

Smarter Cars, Better Robots: NVIDIA’s New Tools for the Physical World

X-BOTS — Thu, 26 Feb 2026 08:39:50 +0000

The “ChatGPT Moment” for Robots

In a major announcement at CES 2026, NVIDIA CEO Jensen Huang declared that we have reached the “ChatGPT moment” for Physical AI. While traditional AI lives inside screens and chats, Physical AI is designed to live in the real world—powering machines that can see, reason, and move just like humans do. To lead this revolution, NVIDIA has moved beyond just making chips. They have released a massive suite of open-source models and tools to help every company—from car manufacturers like Mercedes-Benz to robotics pioneers like Boston Dynamics—build smarter autonomous systems.

Quick Summary of the Big Moves

Focus Area	Key Innovation	Impact
Self-Driving	Alpamayo Suite	Cars that can “explain” their driving logic in plain English.
Humanoid Robots	GR00T N1.6	Advanced whole-body coordination for human-shaped robots.
World Training	Cosmos Platform	AI-generated “synthetic” videos to train robots safely in virtual worlds.
Hardware	Jetson T4000	A compact AI “brain” that is 4x faster and more energy-efficient.

1. Smarter Self-Driving Cars

NVIDIA has introduced the Alpamayo family of open-source AI models and tools to advance safe, reasoning-based autonomous vehicle development. This suite includes the Alpamayo 1 model, which is the first open vision language action model featuring chain-of-thought reasoning to help vehicles navigate complex, rare driving scenarios known as long-tail edge cases. By simulating humanlike judgment, the technology allows autonomous systems to think through decisions step by step and provide explainable logic for their actions. The ecosystem also provides the AlpaSim simulation framework and a vast collection of physical AI open datasets to support high-fidelity testing and validation. Industry leaders like JLR, Lucid, and Uber are already leveraging these tools to accelerate their level 4 autonomy roadmaps. By making these resources openly available on platforms like Hugging Face and GitHub, NVIDIA aims to foster transparency and rapid innovation across the global automotive research community to ensure safer and more scalable self-driving solutions.

2. Improved Brains for Robots

NVIDIA’s introduction of the Cosmos and GR00T N1.6 models represents a massive leap in how machines interact with the physical world by shifting from rigid programming to intuitive “World Models.” The Cosmos platform acts as a sophisticated simulator that generates highly realistic, physics-accurate videos, allowing robots to observe and learn how objects behave when touched or moved. This “synthetic” training is crucial because it allows a robot to practice complex tasks millions of times in a risk-free virtual environment before ever attempting them in a real factory. Building on this foundation, the GR00T N1.6 model specifically targets humanoid robots, providing them with the advanced whole-body coordination needed to balance, walk, and use human tools with precision. By combining visual reasoning with physical dexterity, these models enable robots to understand social cues and safety contexts, ensuring they can work alongside humans more naturally and safely than ever before.

World Foundation Models for Physical AI

Cosmos Predict

Predict future states of dynamic environments for robotics and AI agent planning.

This world generation model produces up to 30 seconds of high-fidelity video from multimodal prompts.

Cosmos Transfer

Accelerate synthetic data generation across various environments and lighting conditions.

This multicontrol model transforms 3D or spatial inputs from physical AI simulation frameworks, such as CARLA or NVIDIA Isaac Sim, into fully controlled high-fidelity video.

Cosmos Reason

Enable robots and vision AI agents to reason like humans.

This multimodal vision language model (VLM) leverages prior knowledge, physics understanding, and common sense to comprehend the real world and interact with it.

NVIDIA Isaac GR00T N1: An Open Foundation Model for Humanoid Robots

NVIDIA’s introduction of the GR00T N1.6 represents a major shift in how machines interact with the world, moving from rigid code to intuitive “Vision-Language-Action” (VLA) models. This specific version acts as a sophisticated brain that processes visual data and natural language instructions simultaneously to control a robot’s entire body. Unlike previous versions, N1.6 uses a much larger “diffusion transformer” architecture—think of it as a deeper neural network—that allows for significantly smoother and more fluid movements. This allows human-shaped robots to perform “loco-manipulation,” which is the complex ability to walk and use their hands at the same time, such as opening a heavy door while stepping through it. By training on thousands of hours of diverse data, ranging from bimanual arm movements to full-body coordination, GR00T N1.6 can generalize its skills. This means a robot trained in a virtual warehouse can more easily adapt to a real-world kitchen or factory floor without needing to be reprogrammed for every new task.

3. Powerful New Hardware

To provide the massive computing power required for these new AI models, NVIDIA launched the Jetson T4000 module, built on the cutting-edge Blackwell architecture. Priced at $1,999, this hardware is designed to be the “intelligent core” for the next generation of autonomous machines. It delivers a staggering 1,200 TFLOPS of AI performance, which is a 4x leap over the previous Orin generation, while maintaining a compact and energy-efficient 70-watt power envelope. This efficiency is critical for battery-powered robots that must process heavy generative AI and real-time sensor data—like LIDAR and multiple 4K cameras—without overheating or draining power too quickly. By bringing data-center-level “reasoning” capabilities directly to the edge, the T4000 allows robots to operate independently of the cloud, ensuring they can make split-second safety decisions even in areas with poor internet connectivity.

Reference

NVIDIA

The Ceiling is the New Floor: How AutoPallet is Flipping the Script

X-BOTS — Thu, 12 Feb 2026 01:40:07 +0000

AutoPallet Robotics, a Y Combinator 2024 startup, publicly demonstrated its novel palletizing and depalletizing system at Manifest 2026. The company’s approach replaces traditional floor-based robotic arms with small autonomous mobile robots that operate upside down, magnetically attached to a steel ceiling structure above the workspace. These robots use vacuum grippers to pick up boxes from pallets or conveyors, lift them overhead, and transport them to designated drop locations. Installed via a freestanding modular superstructure that bolts into existing warehouse floors, the system enables high-density sortation and palletizing without requiring major facility redesigns. By moving automation complexity to the ceiling, AutoPallet allows tightly packed pallets and conveyors below, achieving greater floorspace efficiency and flexibility than conventional loop sorters, tilt-tray systems, or arm-based cells.

AutoPallet Builds Self-Contained Robot Pods

AutoPallet’s system consists of fully self-contained, battery-powered robot pods, each with a mobile base and a separate gripper unit that communicate wirelessly. The base handles propulsion and primary computing, while the gripper—equipped with its own battery, vacuum pump, cameras, and sensors—manages box pickup and placement. Robots coordinate through a wireless mesh network to share tasks and avoid collisions, and they use swappable lithium iron phosphate batteries or autonomous charging to minimize downtime. The company is also developing its own simulation and orchestration software, combining AI techniques from both robotic arms and autonomous mobile robots by effectively using an AMR as a gantry-style robot.

A New Take On an Old Concept

AutoPallet says its system allows multiple ceiling-mounted robots to work in the same area at the same time, unlike traditional overhead gantries that typically use only one gripper per workspace. Similar overhead mobile gripper systems were tried in the 1980s and 1990s, including RobotWorld and others, but they struggled with complex path planning, tangled power and air cables, and lower throughput compared to robotic arms. AutoPallet avoids these issues by using onboard batteries and built-in vacuum systems, eliminating the need for external cables and air lines. The company is demonstrating its system at Booth 2371 at Manifest in Las Vegas.

Key Points On Why AutoPallet’s Approach is Advantageous

Multiple overhead robots allow for higher throughput, operating simultaneously in the same workspace and significantly increasing productivity compared to single-gantry systems. Mounting robots on the ceiling improves space utilization, freeing up valuable floor area and allowing pallets and conveyors to be packed more densely. The system offers scalability, as capacity can be expanded easily by adding more robots to the overhead network. Built-in batteries and vacuum systems reduce complexity, eliminating the need for external cables and air lines and minimizing maintenance challenges. Finally, the modular superstructure supports retrofit-friendly deployment, enabling installation in existing warehouses without major facility redesigns.

Reference

AutoPallet Robotics

The Factors Shaping the Future of Physical AI

X-BOTS — Tue, 27 Jan 2026 08:46:59 +0000

Math Becomes the Engine of Robotics

The next major leap in robotics will come from math, not hardware. Today’s robots are largely reactive, responding to inputs in real time. The next generation will anticipate outcomes before acting.

Emerging mathematical techniques like dual numbers and jets are reshaping how change is modeled. They capture not only motion, but how that motion propagates through an entire system, enabling faster optimization, richer scenario planning, and more adaptive control.

This makes it possible for robots to evaluate path adjustments or run multiple “what-if” scenarios in milliseconds. While these approaches are still mostly confined to research, they represent a natural evolution in how derivatives and system behavior are computed—and their potential impact on robotics is significant.

Predictive intelligence is set to define the next generation of automation; the real question is not whether this shift will occur, but how quickly it will happen and who will emerge as the leaders driving it.

Robots Evolve from Isolated Units to Learning Teams

Imitation learning is set to become a defining capability in the next wave of automation. Today’s robots largely operate as isolated units, relying on centralized control or fixed programming.

The next shift will enable robots to learn from humans and from each other, forming adaptive teams that share behaviors in real time. Building on early research and existing fleet coordination, imitation-learned models will allow robots to coordinate, adapt, and reconfigure workflows without rigid scripts.

As communication, safety, and orchestration tools mature, imitation-driven collaboration will move from pilot projects to real deployments, transforming robots into cooperative, continuously learning systems.

Task-Specific AI Replaces General-Purpose Platforms

Manufacturers are moving away from generic AI platforms toward task-specific AI built for individual processes such as welding, sanding, inspection, and assembly. These vertical AI systems come pre-trained and pre-integrated, delivering measurable gains from day one and enabling automation in tasks once considered too variable or complex.

Welding is already a leading example, with AI-driven vision, seam tracking, and parameter optimization reshaping the process. Similar advances are now extending to more dexterous tasks like assembly, fastening, and intricate handling, where AI helps robots manage variability in parts and workflows.

Logistics has seen rapid progress as well, with AI-powered robots performing complex pick and stow operations at scale. Next, these investments are expected to expand into retail, pushing robotic automation closer to everyday environments.

Robot Data Becomes a Scalable Asset

The next shift in robotics will be driven by how data creates value. Today, most robot data stays on the edge for privacy and performance, limiting its use in training smarter AI.

Secure, opt-in data exchanges will allow anonymized performance data to be aggregated and shared with strong safeguards. Insights from processes like welding or sanding can power better models for defect detection, predictive maintenance, and adaptive control.

By converting raw telemetry into structured, privacy-preserved insights, manufacturers unlock new revenue and continuous improvement, while customers gain AI trained on real-world conditions—creating a cycle where every robot makes the next generation smarter.

References

www.therobotreport.com

Driving the Future of Cargo Logistics with AGVs

X-BOTS — Thu, 15 Jan 2026 01:23:57 +0000

How AGVs Are Transforming Cargo Logistics

In today’s fast-moving global economy, cargo logistics must be faster, safer, and more reliable than ever before. As shipment volumes grow and labor challenges increase, logistics operators are turning to Automated Guided Vehicles (AGVs) to stay competitive. AGVs are reshaping how goods move across airports, seaports, and warehouses—bringing efficiency, automation, and intelligence to every stage of the cargo journey.

Smarter Cargo Movement Across the Supply Chain

Unlike traditional material-handling equipment, AGVs operate autonomously, following optimized routes and working seamlessly with digital logistics systems. This allows businesses to automate repetitive transport tasks, reduce errors, and maintain consistent performance around the clock. The result is smoother cargo flow, faster turnaround times, and greater operational visibility.

Transforming Air Cargo Operations

Figure 1: Lödige Cargo Management System at Shanghai Pudong Airport.

In air cargo terminals, speed and precision are critical. AGVs are increasingly used to transport heavy pallets and Unit Load Devices (ULDs) efficiently and safely. At Shanghai Pudong International Airport, China Eastern Air Logistics implemented high-capacity AGVs from Lödige Industries to automate cargo movement within its terminal. These vehicles operate 24/7 and are fully integrated with cargo management systems, enabling real-time tracking and optimized workflows. This level of automation helps airlines handle growing cargo volumes while improving reliability and reducing manual handling risks.

Driving Efficiency in Seaports

Figure 2: AGVs transporting containers at Hamburg’s Altenwerder Terminal.

Seaports are embracing AGVs to support fully automated container terminals. By transporting containers between quay cranes and storage yards, AGVs improve safety and keep operations running smoothly—even under heavy traffic conditions. At Hamburg’s Container Terminal Altenwerder, AGVs work in perfect coordination with automated cranes, helping the terminal increase throughput and reduce vessel turnaround times. For port operators, this means faster operations, lower costs, and improved sustainability.

Powering the Future of Warehousing

Figure 3: Kiva mobile robots and automated shelving systems in a warehouse.

In warehouses and distribution centers, AGVs have become essential to meeting the demands of e-commerce and omnichannel logistics. Companies like Amazon use autonomous robots to bring shelves directly to workers, dramatically reducing order processing times and improving accuracy. This approach enables faster deliveries, better space utilization, and scalable operations during peak seasons.

Why AGVs Matter for the Future

Across air, sea, and land logistics, AGVs deliver clear business benefits:

Faster and more predictable operations
Safer working environments
Reduced operational costs
Improved scalability and flexibility

More importantly, AGVs enable logistics providers to build future-ready operations that can adapt to changing market demands.

Conclusion

AGVs are not just automating cargo movement—they are transforming the logistics industry. By combining automation with intelligent software, AGVs help businesses move goods more efficiently, operate more safely, and remain competitive in an increasingly complex global supply chain.

Reference

www.lodige.com

Autonomous Robots with Multi-sensor futuristic in AI-tech

Editor — Mon, 04 Aug 2025 09:53:18 +0000

Autonomous robots and unmanned vehicles require precise positioning to navigate efficiently, yet many existing solutions highly depend on costly HD maps, 3D LiDAR, or GNSS/RTK signals. oToBrite’s innovative multi-camera vision-AI SLAM system—oToSLAM—provides a breakthrough alternative by ensuring reliable mapping and positioning in both indoor and outdoor environments without the need for external infrastructure.

Utilizing four automotive-grade cameras, an edge AI device (<10 TOPS), and advanced vision-AI technology, the system integrates key technology such as object classification, freespace segmentation, semantics and 3D feature mapping with optimized low-bit AI model quantization and pruning. This cost-effective yet high-performance solution achieves positioning accuracy of up to 1 cm (depending on the environment and use of additional sensors), outperforming conventional methods in both affordability and precision.

When we talk about vision SLAM technology, the most common major challenge we encountered was the limitation of traditional CV-based SLAM. While this technology is computationally efficient, their accuracy and adaptability across diverse environments were insufficient for real-world deployment. In particular, CV-based approaches struggled in scenarios with low-texture scenes, dynamic objects, and varying lighting conditions, leading to degraded localization performance. After extensive testing and evaluation across multiple use cases, we ultimately chose to adopt vision-AI SLAM technology. By leveraging deep learning, we were able to extract more robust and meaningful 3D features, significantly improving positioning accuracy and environmental adaptability. This transition to AI-driven SLAM allowed us to build a solution that not only performs reliably in complex environments but also scales effectively for mass production and long-term maintenance.

However, implementing AI algorithms on the TI TDA4V MidEco 8-TOPS platform presented new challenges. The model processes images layer by layer to generate features, but not all layers are nativelysupported on the production platform. While standard layers such as CONV and RELU are compatible, others require custom development. To bridge this gap, we created additional algorithm packages to ensure compatibility and preserve model functionality while adapting it for real-world deployment.

Another key challenge we faced during the transition to mass production was the limitation of relying solely on non-semantic feature points generated by the model. Although these 3D feature points are highly repeatable and robust across varying perspectives, they lack semantic context—such as identifying curbs, lane markings, walls, and other critical environmental structures. Through comprehensive analysis across diverse driving scenarios, we found that combining 3D non-semantic features and semantic feature points significantly improves the precision and robustness of our VSLAM system. This hybrid approach allows us to leverage the geometric stability of non-semantic features while enhancing environmental understanding through semantic context. As a result, integrating both feature types within the VSLAM pipeline have become a core strategy in overcoming the limitations of pure 3D point-based tracking. It plays a vital role in achieving higher accuracy, consistency, and resilience—especially in complex, dynamic environments—and serves as a key differentiator for our solution in the market.

Optimizing AI-based VSLAM models involves several challenges, including high computational complexity, difficulty in generalizing across diverse environments, and handling dynamic scenes. To overcome these, we adopt lightweight neural network architectures and quantization techniques for real-time performance on edge devices. Furthermore, we are not just optimizing the VSLAM models for 3D feature extraction, but also adding value with semantic features extraction via customized lightweight object classification and image segmentation. In the end, we enable multi-camera vision-AI SLAM from research to edge AI device mass production for autonomous robots and unmanned vehicles

Learn more about oToSLAM: https://www.otobrite.com/pr oduct/otoslam-vision-ai-positioning-system

Appendix

Reference Models

The following models were referenced during the development process:

ORB-SLAM: a Versatile and Accurate Monocular SLAM System

LIFT: Learned Invariant Feature Transform

SuperPoint: Self-Supervised Interest Point Detection and Description

GCNv2: Efficient Correspondence Prediction for Real-Time SLAM

R2D2: Repeatable and Reliable Detector and Descriptor

Use of a Weighted ICP Algorithm to Precisely Determine USV Movement Parameters

Visual SLAM are replacing for the Bigger tech company ABB

Editor — Wed, 30 Jul 2025 08:32:59 +0000

ABB this week said it is extending its portfolio of fully autonomous mobile robots, or AMRs, by equipping its Flexley Mover P604 with 3D visual simultaneous localization and mapping, or vSLAM, navigation and user-friendly AMR Studio programming software. The Zurich-based company said the launch is part of its overall effort towards offering robots that are more versatile, efficient, and easier to use.

“ABB has perfected robot eyes, through 3D AI vision technology; hands, through advanced force sensing, precision dexterity, and machine learning; and independent mobility, through 3D mapping,” stated Marc Segura, president of ABB Robotics. “Fusing these technologies gives our robots a complete and dynamic understanding of the world around them, enabling safer, more intelligent, and autonomous operations for our customers across automotive, manufacturing, and logistics.”

ABB’s product line includes a full range of industrial robots, collaborative robot arms, and AMRs (acquired with ASTI in 2021). Last year, it acquired Sevensense, which provided navigation capabilities for its AMRs, rebranded as the Flexly line. ABB Robotics is one of the top RBR50 winners of all time, earning recognition every year in the innovation award’s history.

In April, ABB Group announced that it would be spinning off its entire robotics division. It intends for the business to start trading as a separately listed company in the second quarter of 2026. The company missed its revenue prediction for the first quarter of 2025 by $260 million and acknowledged that macroeconomic uncertainty from tariffs has affected its business.

ABB simplifies programming with AMR studio

ABB designed its Flexley Mover to lift and transport objects of various payloads in a variety of settings. This can enable greater efficiencies in applications like intralogistics and kitting operations. ABB said the system is accurate to within 10 mm (0.3 in.), and is matched to an AI learning algorithm.

This algorithm enables each robot to generate maps of its workspace and securely share this knowledge with other robots in its fleet. This enables fully independent, flexible, and scalable navigation alongside human workers, with no need for additional infrastructure, ABB said. The technology also allows robots to perform complex tasks such as goods-to-robot operations, line supply/kitting, and inter-process connection.

In addition, ABB said the capabilities of 3D AI vision are further amplified by its AMR Studio software. This provides a user-friendly platform for creating and configuring routes and tasks for AMRs, from standalone units through to entire fleets.

With simplified programming and graphical interfaces, the software reduces commissioning time by up to 20% compared with conventional systems, with potential cost savings of up to 30%, claimed the company. Throughout this year, ABB said it will continue fusing its precision hardware with artificial intelligence and software, towards further autonomy and versatility.

“We’re in a new era of robotics innovation. Robots that can do more things, in more places, and do it faster, safer, and smarter, directly open the door to greater productivity and eliminate the need to invest in specialist skills or infrastructure,” Segura said. “With our 50-year heritage as the original robotics innovator, we remain at the forefront of not just developing the latest technologies, but also engineering them for commercial use, at scale.”

ABB will introduce P604 Visual SLAM & AMR Studio in Booth 2632 at the Automate trade show in Detroit next week.

Can Robots Fix the Warehouse Worker Shortage? ProMat 2025 Says Yes

Editor — Fri, 11 Jul 2025 06:44:28 +0000

The cavernous halls of McCormick Place in Chicago played host to ProMat 2025, a sprawling testament to the relentless innovation shaping the future of manufacturing and supply chain. This year’s exhibition, held from March 17th to 20th, resonated with a palpable urgency, driven by a challenge that casts a long shadow over the industry: the persistent and intensifying labor shortage in warehousing and logistics. While ProMat has always been a showcase of cutting-edge technology, the 2025 edition felt particularly focused on solutions designed to alleviate the strain on human capital, with robotics taking center stage as a powerful and increasingly viable answer. The warehousing and logistics sector has been grappling with a growing labor crisis for years, a situation exacerbated by factors ranging from an aging workforce and demanding physical labor to increased e-commerce volumes and evolving worker expectations. High turnover rates, recruitment difficulties, and the sheer volume of work required to keep supply chains flowing have created a critical need for automation. ProMat 2025 served as a crucial platform for businesses seeking tangible solutions to this pressing issue, and the sheer number and sophistication of robotic offerings were a clear indication of the industry’s direction.

The Rise of Warehouse Robotics: A Multifaceted Approach

Robotics in the warehouse is no longer a futuristic concept; it is a rapidly evolving reality, offering a spectrum of solutions tailored to various operational needs. ProMat 2025 provided a comprehensive overview of the current state-of-the-art, highlighting several key areas where robotics is making significant inroads in addressing labor challenges:

Dense Storage Solutions: Maximizing Space and Automation

With warehouse space at a premium and the need for efficient storage increasing, dense storage solutions integrated with robotics are gaining significant traction. Robotic Automated Storage and Retrieval Systems (AS/RS) were prominently featured, demonstrating their ability to maximize storage density while automating the putaway and retrieval of goods. These systems, often utilizing vertical space and intricate robotic movements, reduce the need for extensive aisle space and manual picking, thereby minimizing labor requirements and increasing throughput. The integration of sophisticated software allows for optimized storage strategies and faster order fulfillment, directly addressing the need for efficiency in the face of labor constraints.

Autonomous Mobile Robotics (AMRs): Intelligent Movement and Task Execution

Autonomous Mobile Robots (AMRs) have emerged as a versatile solution for a wide range of warehouse tasks. Unlike traditional Automated Guided Vehicles (AGVs) that rely on fixed pathways, AMRs utilize advanced sensors, cameras, and mapping software to navigate autonomously around obstacles and optimize routes in dynamic warehouse environments. ProMat 2025 showcased AMRs performing tasks such as goods-to-person picking, transporting materials, and even assisting with pallet movement. Their flexibility and ability to adapt to changing layouts and tasks make them a powerful tool for augmenting human labor and improving overall efficiency. By taking over repetitive and physically demanding transportation tasks, AMRs free up human workers for more complex and value-added activities.

Aerial Inventory Management: The Eyes in the Sky

While still a developing area, drone technology for warehouse inventory management was also present at ProMat 2025, highlighting its potential to address the time-consuming and often hazardous task of manual inventory checks. Autonomous drones equipped with cameras and scanning technology can navigate warehouse aisles, capture inventory data, and identify discrepancies with greater speed and accuracy than human workers. This technology not only reduces the labor required for inventory management but also provides real-time insights into stock levels, minimizing errors and improving overall inventory accuracy.

Robotic Picking: Precision and Versatility in Order Fulfillment

The picking process, a labor-intensive and often error-prone aspect of warehousing, is a prime target for robotic automation. ProMat 2025 featured a diverse array of robotic picking solutions, ranging from stationary robotic arms integrated with vision systems to mobile robots equipped with grasping capabilities. These robots are increasingly sophisticated, capable of handling a wide variety of items with different shapes, sizes, and textures. Advanced AI and machine learning algorithms enable them to identify and grasp items accurately, improving order fulfillment speed and reducing picking errors, directly mitigating the impact of labor shortages in this critical area. Collaborative robots (cobots), designed to work safely alongside human workers, also presented a compelling option for augmenting picking tasks and reducing the physical strain on employees.

A Walk Through Innovation Alley: Booth Highlights

My exploration of the ProMat 2025 exhibition floor provided a tangible understanding of the robotic solutions poised to tackle the labor crisis. Here are summaries of the key displays from the booths I visited:

: Focused on their M5F AMR, highlighting its versatility and applications in warehouse automation, particularly for brownfield implementations.

XYZ Robotics: Showcased their advanced AI-driven robotic picking systems, emphasizing their ability to handle diverse SKUs with high accuracy and seamless integration with other warehouse technologies.

Universal Robots: Emphasized the versatility and ease of use of their collaborative robots (cobots) for various material handling tasks, integrated with a robust UR+ ecosystem.

ForwardX Robotics: Displayed their comprehensive range of vision-based AMRs, including the Flex 600-LS, Apex C1500-L, and Max 1500-L, highlighting their AI-powered navigation and integrated logistics capabilities.

Seegrid: Featured their advanced AMR solutions, particularly the Lift CR1 AMR for high-lift applications, and their “Sliding Scale Autonomy” concept for flexible automation.

Geek+: Showcased their high-density storage solutions and goods-to-person robotics, emphasizing scalability and practical steps for warehouse modernization.

EXOTEC Technologies: Highlighted their next-generation Skypod AS/RS, emphasizing end-to-end automation and scalability.

Ambi Robotics: Demonstrated their AI-powered robotic picking solutions, including AmbiSort and AmbiStack, emphasizing dexterity and precision in handling diverse items.

Tompkins Robotics: Showcased their flexible and efficient tSort robotic sortation systems, adaptable to various warehouse layouts and scalable for changing needs.

Pickle Robot: Conducted live demonstrations of their robotic truck unloading solutions, emphasizing their ability to handle messy piles and the use of “Physical AI.”

KUKA: Unveiled their KMP 3000P heavyweight AMR and demonstrated integrated robotic cells combining AMRs with industrial robots and cobots for enhanced efficiency.

Autostore: Focused on their high-density cube storage AS/RS, highlighting partnerships with Kardex and Element Logic to provide integrated automation solutions.

Berkshire Grey: Showcased their AI-powered robotic picking solutions, the V3 Robotic Put Wall, and the RPSi robotic package sortation system, emphasizing end-to-end automation.

Agility Robotics: Demonstrated the capabilities of their humanoid robot, Digit, performing autonomous tasks like tote loading and unloading, highlighting the potential of humanoid robots in material handling.

Brightpick: Provided live demonstrations of their Brightpick Autopicker for in-aisle robotic picking and order consolidation, emphasizing its versatility and AI-powered vision.

Hai Robotics: Displayed their HaiPick Climb system for goods-to-person automation in existing warehouses and the HaiPick System 3 for high-density storage and throughput.

Attabotics: Highlighted their 3D robotic AS/RS and their new “Fulfill” AI-orchestrated fulfillment software, emphasizing efficiency and density.

Slip Robotics: Showcased their SlipBot automated loading robots for truck loading and unloading, emphasizing speed, safety, and ease of integration without IT infrastructure changes.

SEER Robotics: Debuted their SPT-1000 autonomous pallet truck with AI-powered pallet recognition and showcased their SRC robot controllers and software solutions.

MyBull Intelligent Machinery: Demonstrated their range of AMR solutions, including autonomous tow tractors and unmanned forklifts for various industrial logistics applications.

Libiao Robotics: Featured their AMR-based parcel sortation systems, emphasizing flexibility, scalability, and high-speed, accurate sorting capabilities.

Corvus Robotics: Showcased their autonomous drone system for inventory management, highlighting their integration partnership with Honeywell and the use of computer vision.

Lab0: Debuted their fully autonomous RoboGlide warehouse system for end-to-end inbound logistics, emphasizing its humanoid-inspired design and AI-powered vision and motion planning.

Yaskawa: Displayed a comprehensive range of industrial robots and cobots for material handling and logistics, highlighting their Pallet Builder software and various application-specific solutions.

Gather AI: Introduced their MHE Vision AI-driven camera system for real-time material handling visibility and analytics, emphasizing warehouse digitization.

Plus One Robotics: Focused on their advanced palletizing and depalletizing solutions, highlighting their partnership with beRobox and the launch of their new Partner Portal.

FANUC: Presented a wide range of robotic solutions for warehousing and logistics, including mobile robotic order fulfillment, full-layer depalletizing, and tote consolidation.

Locus Robotics: Introduced LocusINTELLIGENCE AI-driven business intelligence software and showcased their Locus Array fully robotic zero-touch fulfillment system.

Ocado Intelligent Automation (OIA): Featured their OSRS, the debut of the Porter AMR, the Chuck AMR, and OCADEX robotic pick arms, emphasizing integrated automation solutions.

Oceaneering Mobile Robotics (OMR): Showcased their MaxMover and UniMover AMRs for industrial applications and strategies for seamless AMR integration.

Zebra Technologies Displayed their end-to-end solutions for warehouse and supply chain optimization, including mobile computers, barcode scanners, RFID, AMRs, vision systems, and software.

Multiway Robotics: Highlighted their advanced AMR forklift solutions, including the X20S, SE15, and Q20 models, emphasizing versatility and heavy-duty capabilities.

Anyware Robotics: Won the MHI Innovation Award for their Pixmo Mobile Robot designed for autonomous truck unloading and palletization.

The Automation can help the retailer optimise it workload

Editor — Wed, 09 Jul 2025 05:54:53 +0000

When French retailer Boulanger was looking for a way to automate its warehouse fulfillment process, managers turned to Locus Robotics and its LocusOne platform for a scalable solution that would fit with the company’s digital transformation strategy. That decision to go with Locus has yielded big results for the seller of consumer electronics and appliances, including a triple-digit productivity increase, and has led to plans to apply the artificial intelligence (AI)-driven mobile robotics solution to more warehouse processes.

A RAPID DEPLOYMENT – Boulanger installed Locus Robotics’ collaborative autonomous mobile robots (AMRs) for picking at its Hénin-Beaumont warehouse, located in northern France. The facility manages a broad range of consumer electronics and home appliances, distributing stock to more than 200 stores across the country. Managers say the deployment has enhanced workforce efficiency, as warehouse associates work alongside the AMRs—the robots do the heavy lifting and traveling through the aisles, reducing the amount of time associates spend on those tasks and, thus, speeding fulfillment. The AMRs, which run on the AI-driven LocusOne software platform, were installed in less than four months and seamlessly integrate with Boulanger’s warehouse management system (WMS) and its existing material handling equipment—ensuring smooth operations without disrupting established workflows, according to both companies.The quick installation was followed by fast results: Within six weeks of going live with the system, Boulanger had doubled its picking productivity.

SOLID RESULTS – The scalability of the solution has been a boon to Boulanger’s business as well: Locus was able to respond to the recent 30% surge in business by quickly adding AMRs to the fleet. Locus Robotics’ robots-as-a-service (RaaS) model makes that possible, allowing companies to scale up without the burden of large capital investments. The results speak for themselves: Within six weeks, productivity at the Hénin-Beaumont facility soared from 120 units processed per hour to more than 250. In addition, the facility has processed nearly 9 million units in less than a year, “demonstrating exceptional efficiency,” according to both companies. “Boulanger’s rapid transformation showcases how flexible automation can revolutionize fulfillment operations,” Denis Niezgoda, chief commercial officer, international at Locus Robotics, said in the release. “By integrating LocusOne, Boulanger has gained the scalability, efficiency, and agility required to meet growing customer expectations. This deployment reinforces our commitment to supporting France’s evolving logistics landscape with intelligent, scalable automation solutions.” And now the partners are turning their attention to new applications.

Understanding the Various Kinds of AGVs and AMRs industry insider

Editor — Mon, 07 Jul 2025 02:21:31 +0000

Looking for the latest innovations in automated material handling? We’ve rounded up the latest crop of Autonomous Mobile Robots (AMRs) and Automated Guided Vehicles (AGVs).

Lift RS1 AMR: Seegrid’s vision-guided autonomous lift truck is capable of a 6-foot lift height and has a payload capacity of 3,500 pounds. The RS1 features Seegrid’s Sliding Scale Autonomy, which combines the agility of autonomous mobile robots (AMRs) and the predictability of automated guided vehicles (AGVs). This allows the truck to navigate differently based on what is best suited for the specific customer application at hand.

Stretch: Boston Dynamics’ Stretch autonomous robot unloads floor-loaded trailers and shipping containers, keeping the flow of goods moving in warehouses. The AMR can unload continuously for up to 16 hours, move hundreds of cases per hour, up to 50 pounds, and grasp multiple cases at once. Stretch is operating in the field with customers including DHL, Gap, H&M, Otto Group, Maersk, and NFI.

Geek+ SkyCube: The pallet-to-person solution combines upper-level storage and ground-level picking technology. The multilevel storage and retrieval system can increase warehouse throughput, storage capacity, operational flexibility, and integrate with intelligent equipment (unstacking machine, automatic wrapper or packer, robotic arm, etc.) to realize an unmanned smart warehouse

A10 Flexible Forklift: Muratec’s A10 Flexible Forklift is a versatile AGV that can streamline materials handling in dynamic warehouse environments. With a maximum lift height of 32 feet and a 3,300-pound load capacity, it navigates narrow aisles, optimizes storage, and automates load transfers. Featuring multiple navigation options, including laser guidance, the A10 adapts to warehouse layouts without disrupting infrastructure.

OMRON LD Series Robots: The LD Series AMRs from OMRON now work with wireless charging technology from Wiferion. The inductive charging technology enables fast charging up to 60amps and charges the AMRs from the underside without interrupting work processes. RAMP, a Samuel Automation company and integrator, recently implemented the technology at an automotive manufacturing facility.

Simplimatic AMR: The AMR from Signode is an integrated system with a mobile platform and collaborative robotics. Featuring self-guided navigation, it adapts to existing facility layouts and reroutes around obstacles for uninterrupted material flow. With high load capacity, automatic charging capabilities, and a compact footprint, the customizable solution can work in tandem with the Simplimatic robotic palletizer and depalletizer to handle diverse loads

Dematic Goods-to-Person AMRs: The D30 Tote Mover AMR (left) and D50 Masted Tote Shuttle AMR (right) optimize order fulfillment with the goods-to-person approach. The Tote Mover AMR streamlines tote transport, offering precision and eliminating single points of failure. The Masted Tote Shuttle AMR offers high-speed, automated storage and retrieval capabilities measuring up to approximately 40 feet high.

HaiPick Climb: The new HaiPick Climb system from Hai Robotics is built around the HaiClimber robot (below), an intelligent, compact climbing robot. HaiPick Climb operates by attaching climbing channels to one side of nearly any industry-standard racking. Robots travel up and down these channels, retrieving totes from both sides of narrow aisles. With the HaiClimber robots traveling at a speed of 13 feet per second and climbing at 3 feet per second, the HaiPick Climb system can process 4,000 totes per hour within a 1,000-square-meter (10,764-square-foot) space.

Yale Relay Automated Lift Trucks: Yale Relay automated lift trucks don’t require custom code or intensive engineering. A drag-and-drop portal allows for implementation in as little as one day and gives warehouses the control to make changes on the fly. The rental model is designed to offer financial flexibility and a clear return on investment, supporting deployment without a large capital outlay or hidden costs.

Xbots: this is the immortal robot, no matter manual handle or rely on it program

Warehouse Automation Market expected to be grow and exponentially expand until 2030

Editor — Fri, 04 Jul 2025 02:12:38 +0000

Key Market Drivers Fueling the Growth of the Autonomous Mobile Robot (AMR) Market — The global Autonomous Mobile Robot (AMR) market is witnessing significant momentum, driven by a confluence of critical factors reshaping the logistics and manufacturing landscape. From labor shortages to the e-commerce boom, AMRs are emerging as a transformative solution across industries. Increased Operational Efficiency Businesses across the globe are turning to AMRs to enhance operational efficiency and streamline workflows. By automating routine tasks and material handling, these robots are enabling companies to reduce reliance on manual labor while increasing productivity and accuracy. Labor Shortages Accelerating Adoption Ongoing labor shortages in key sectors such as logistics, manufacturing, and retail have further accelerated the adoption of AMRs. Companies are investing in automation to maintain productivity in the face of staffing challenges, making AMRs a critical asset in modern operations. Technological Advancements Driving Capabilities Rapid advancements in artificial intelligence (AI), machine learning, and sensor technology have made AMRs more intelligent, adaptable, and reliable. These innovations are expanding the functional capabilities of AMRs, allowing them to navigate complex environments and make real-time decisions with minimal human intervention. E-Commerce Boom Boosting Demand The continued surge in e-commerce has intensified the need for efficient warehouse and inventory management systems. AMRs are playing a pivotal role in meeting these demands, offering scalable solutions for picking, sorting, and transporting goods in high-volume fulfillment centers. As these key drivers continue to shape the market, the AMR sector is poised for sustained growth, with more companies embracing automation as a strategic imperative for competitiveness and resilience.

Autonomous Mobile Robots (AMRs) are gaining traction across diverse sectors, with warehouse automation leading the charge. Expected to account for over 75% of the market by 2030, AMRs are transforming inventory and order fulfillment processes. In manufacturing, AMRs are gradually replacing traditional AGVs, offering greater flexibility for material handling and assembly line operations. Meanwhile, in healthcare, AMRs are emerging as a high-growth niche, streamlining the transport of medical supplies and supporting better patient care. As AMRs prove their value in varied environments, their role in reshaping industries continues to expand rapidly.