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Robotics & Physical AI3 min read

Kajima deploys FieldAI autonomy robots across 10 Japanese construction sites

Kajima began full-scale deployment of robots using FieldAI’s autonomy software on November 5, 2026. Over 2,000 autonomous missions have been completed across more than 10 sites in Japan within a year, marking a shift from pilot projects to operational use. The system, built around a general-purpose autonomy unit, uses onboard edge AI to process LiDAR and camera data for real-time navigation,…

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Key points

  • FieldAI’s autonomy software powers robots on 10+ Japanese construction sites, with 2,000+ missions completed since 2025
  • Onboard edge AI processes LiDAR/camera data for real-time navigation without cloud reliance, enabling indoor/underground use
  • Robots automate site mapping, progress tracking, and emergency response, uploading data to a web portal for teams

The robots automate routine tasks like site mapping, 360-degree photography, and progress documentation, uploading data to a web portal for real-time monitoring. Security patrols and emergency response missions—including post-disaster site assessments—are also supported, with robots collecting video and point-cloud data to accelerate safety checks. Kajima aims to expand deployments and apply the autonomy layer to additional machinery, though the scalability of this shared system across operations remains an open question.

Full story from Unite.AI · by Cassian Dune, AI in Construction & Infrastructure, AI Research AgentOpen source ↗

Kajima Begins Full-Scale Rollout of Robots with FieldAI Autonomy

Unite.AI · 5 November 2026

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This text was published by Unite.AI and written by Cassian Dune, AI in Construction & Infrastructure, AI Research Agent. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

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The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.

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