Sign Up Now: AI & Robotics Days – Munich

Digital Intelligence Drives Autonomous Logistics

Generative AI, Digital Twins & Autonomous Robotics – experience them live in Munich.

Choose your preferred date: 16 or 17 September 2026 | from 10:00 a.m. to approx. 3:30 p.m. CEST | Conference language: German

Logivations and Pixel Robotics present their innovative solution portfolio at a joint live event.

KEY TOPICS: Digital Twin, Generative AI & Autonomous Robotics

I. Demonstration Digitaler Zwilling in der Praxis
  • Digital Twin as the tool for design, simulation & optimization
  • Scenario simulation, heatmaps, 3D load preview, what-if analyses
  • Intelligent optimization algorithms: product placement, tour building, case pack and case portfolio optimization, warehouse capacity optimization
  • Supply Chain Engineering for current changes in the supply chain
  • NEW: Generative AI integration – interaction in natural language, intelligent scenario generation, automatic estimation of optimization potential
  • Case studies & anonymous customer examples
Warehouse network map and Digital Twin 3D view
Overhead camera view of a warehouse with robots and pallets
II. Real-Time Digital Twin, Fleet Management and AI-based Recognition
  • Scan-Free Logistics: tracking of all goods movements, occupancy of storage areas and bin locations
  • Localization of all objects without tags
  • Measuring and counting objects, text reading and identification of properties
  • Safety at Work: detection of dangerous situations (indoor and outdoor) and monitoring compliance with safety regulations
  • Fleet Management: control of forklifts, AGVs and AMRs based on the Digital Twin with minimal interfaces required. NEW: definition of rules in natural language
III. Autonomous Transport Robot Pixel PT & AI-based Navigation
  • Real Time Digital Twin: the camera system can detect not only robots but also all relevant objects in the warehouse – ensuring full process transparency and 100% inventory accuracy at all times.
  • Fleet and Area Management: for mixed fleets (forklifts, AGVs, AMRs, tugger trains, etc.)
  • Transport Order Generation via Natural Language: a new level of autonomy
  • Obstacle Avoidance and Dynamic Navigation: enabled by visual recognition of travel paths
    • Control via natural language using Generative AI
    • AI-supported path planning and obstacle avoidance
    • Handling of inaccurately placed pallets
    • Detection and penetration of wrapped pallets
  • Robust Hardware and Battery Capacity: designed for operation across more than 2 shifts
Pixel Robotics forklift robot in a warehouse, and a render showing fork detection

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