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AI, robotics & futureFuture · Die Firma aus Systemen10,000 AI agents as a scaling target, networked tasks and an interactive estimator.
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AI, robotics & futureRobotics · 10 platformsManufacturers, capabilities, interfaces and integration tasks.
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MSD Direct & MarktplatzMSD Direct · Das PortalPeople, opportunities, way of life.
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MSD WORLDSiteWarden · Robotics LabGripping, sensor technology and physical AI – planned experimental programs.
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MSD / TECHNOLOGY / RESEARCH EDITION
A robot is just a building block. Cameras and sensors record the environment, software processes information, AI supports decisions and a controller carries out permitted actions. We show how these levels work together – and what task each of them has to solve.
RECHERCHESTAND 12.11.2026 · FAKTEN + EINORDNUNG + SZENARIENMSD / TECHNOLOGY / DARUM GEHT ES
A digital assistant can prepare documents, find knowledge and classify structured requests. With suitable interfaces, this becomes a workflow between email, CRM and ERP. Authorizations, data quality and approvals determine whether a helpful draft can be safely processed further.
Robotic arms, mobile platforms and specialized machines handle different tasks. Grippers, cameras, force sensors and material feed must fit the environment. A repeatable extraction from a prepared device is technically different than cleaning up in an unknown workshop.
We want to work with customers to develop the connection between their process and suitable technology: record the task, describe requirements, check platforms and interfaces, plan a limited trial and define success criteria. Professional acceptance and safe operation are part of it right from the start.
01 / FROM THE NINEties TO THE NEXT SYSTEM
Information becomes linkable.
Research note ↗1997A clearly bounded task space delivers spectacular performance.
Research note ↗2017Sequences gain a new technical foundation.
Research note ↗2022Planning, observing and acting form a loop.
Research note ↗2023Vision-Language-Action and shared robotics data.
Research note ↗2024Adaptable robotics models and mobile manipulation.
Research note ↗2026Quality, energy, liability and measurable economics.
Research note ↗Historical milestones, not a complete history of technology. Each node leads to source, classification and boundaries.
02 / SYSTEM EXPLORER
Cameras detect parts and open spaces. Depth sensors measure geometry. Force and tactile sensors report contact. Only together can the workspace be in a usable state.
Test question: Does the system also recognize black, shiny or hidden components?
Research on this in the journal ↗A model classifies objects and instructions. Process logic connects the order with status, tools and releases. Linguistic plausibility alone is not enough.
Testfrage: Was passiert bei einer mehrdeutigen Anweisung oder fehlenden Information?
Research on this in the journal ↗A policy creates movements; a robot carries it out within its limits. Gripper, cycle, material supply and safe control determine the throughput.
Test question: How much human intervention does an hour of real work require?
Research on this in the journal ↗Demonstrations and test data make processes trainable. Simulation expands variants. Unknown real-life situations check whether the transmission works.
Test question: Is a success really new - or was the case already in the training data?
Research on this in the journal ↗03 / THE NEXT BUILDING BLOCKS
Force and contact open up tasks that camera images alone cannot solve: insertion, joining, tracking and sensitive surfaces.
Models connect perception and linguistic goals with actions. The open question remains reliable transfer to new environments.
Virtual variants shorten test cycles. Calibration and differences from reality must then be specifically tested.
Short feedback and controlled data paths can justify local processing. Energy and maintenance belong in the same decision.
ERP, documents, communication and rules become an executable process chain. Identities and sharing limits remain essential.
A demonstration only becomes a resilient system through acceptance, repeatability, error handling and support.
04 / ROADMAP, KEIN LIEFERTERMIN
MSD scenario: more integrated assistance and robotics in prepared environments. Condition: sufficient data, secure interfaces and a sustainable process.
MSD scenario: less manual changeover and better transfer between similar tasks. Condition: robust generalization, reliable testing and suitable hardware.
Open research vision: far-reaching coordination of physical and digital work. Timing, limits and economic viability are not certain.