All Foundries

Isometric blue-and-white model of an energy and logistics network with a docked cargo ship, solar panels, factories, office buildings, pipes, trucks, workers, and stacked materials.

Commodity Management & Trading

Transforming trading ecosystems through data-driven insights and secure, agile platforms that empower global commerce.

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Customer & Marketing Strategy

Reimagining customer engagement with personalized, connected experiences that build trust and long-term value.

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Digital Engineering

Turning ideas into scalable digital solutions—accelerating transformation through design, technology, and engineering excellence.

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Station Studio

Redefining mobility hubs with digital innovation to create smarter, sustainable experiences for people and businesses on the move.

Isometric 3D logistics campus with white modern warehouses, blue-green accents, workers, delivery vans, a loading dock, and stacked shipping containers.

Supply Chain & Industry 5.0

Building resilient, intelligent supply networks that anticipate change and deliver efficiency with purpose.

White-and-blue sustainable campus with solar panels, a wind turbine, EV charging stations, loading dock trucks, trees, and small groups of people.

Sustainability

Driving responsible innovation to help organizations achieve net-zero goals and create a positive impact for future generations.

Isometric smart factory scene with white buildings, robotic arms on assembly lines, drones, autonomous carts, workers, control screens, and a fenced power substation connected by blue paths.

Physical AI

Physical AI gives machines, robots and physical operations the ability to perceive their environment, decide what matters and act in real time. Factories, plants, stores and infrastructure become systems able to sense conditions, learn from them and improve on their own, closing the gap between the physical and the digital world.

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Next-Gen Infrastructure

From networks as infrastructure to connected platforms that enable critical, autonomous and intelligent operations.

Robotics Cloud Platform

Manufacturers often run robots from several providers, and every brand demands its own specialist skills. NTT DATA built the Robotics Cloud Platform, an agnostic control layer for robotic arms independent of proprietary systems. ROS and a digital twin simulate each movement, and AI adds new skills before a robot reaches the production line.

Robotics Cloud Platform

Multi-UAV system for autonomous inspection

Critical infrastructure and private areas need constant watching, and fixed surveillance leaves gaps across large sites. NTT DATA applied artificial intelligence to build a multi-UAV system for autonomous patrolling. Reinforcement learning optimizes every flight path, and computer vision designed for bad weather keeps inspection results reliable.

Multi-UAV system for autonomous inspection

Contact

Robotics Cloud Platform

Robot brands: Multi-vendor

One control layer for arms from different manufacturers.

Line testing: Digital twin

Teams simulate the whole production line before go-live.

New capabilities: AI-based

Self-learning of movements and perception from camera and sensor data.

Task assignment: User-driven

Operators pick a robot and assign its task in the production chain.

Robotics Cloud Platform

Robot choice without proprietary lock-in

Objectives

Work with robots from different manufacturers without needing to know the specific characteristics of each one.

Opportunity

Teams pick the robot best suited to each manufacturing need, whatever the brand, and test the line before production starts.

One brand, one skill set

Manufacturing keeps asking for more automation. Each robot provider brings its own control system, so the team needs product-specific knowledge for every brand on the floor.

Key Challenges

1: Mixed fleets. Companies work with several robot providers at the same time.

2: Product-specific skills. Each brand requires its own expertise to program and run.

3: Trials on live equipment. New movements had no safe space for testing before production.

4: Choices tied to the brand. Robot selection followed the installed system more than the manufacturing need.

Solution

An agnostic control platform with a digital twin

NTT DATA built the platform on the ROS framework and a digital twin, using NVIDIA Omniverse, MQTT, OPC UA and Python.

Vendor-agnostic control

One interface controls robotic arms from different manufacturers, on cloud and data center infrastructure NTT DATA designs, builds and operates.

Digital twin simulation

ROS and the digital twin reproduce robot movements so the team develops and tests new capabilities in controlled situations.

AI capabilities

Algorithms add self-learning of movements for new tasks and environmental perception based on camera and sensor data.

Task assignment

Users select the robot of interest and assign its tasks within the production chain.

Impact

Lower production costs and more freedom of choice

Teams supervise, simulate and test the movements of the entire production line before go-live, saving time and cost. Manufacturers choose the robots best suited to their needs, whatever the producer’s brand, and NTT DATA assesses each option on neutral terms. The digital twin combined with Robotics Cloud reduces production costs and increases competitiveness.

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