ADAPT: An Autonomous Forklift for Construction Site Operation

Johannes Huemer, Markus Murschitz, Matthias Schörghuber, Lukas Reisinger, Thomas Kadiofsky +8 more
3/18/2025
cs.ROcs.CVeess.SY

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Abstract

Efficient material logistics play a critical role in controlling costs and schedules in the construction industry. However, manual material handling remains prone to inefficiencies, delays, and safety risks. Autonomous forklifts offer a promising solution to streamline on-site logistics, reducing reliance on human operators and mitigating labor shortages. This paper presents the development and evaluation of ADAPT (Autonomous Dynamic All-terrain Pallet Transporter), a fully autonomous off-road forklift designed for construction environments. Unlike structured warehouse settings, construction sites pose significant challenges, including dynamic obstacles, unstructured terrain, and varying weather conditions. To address these challenges, our system integrates AI-driven perception techniques with traditional approaches for decision making, planning, and control, enabling reliable operation in complex environments. We validate the system through extensive real-world testing, comparing its continuous performance against an experienced human operator across various weather conditions. Our findings demonstrate that autonomous outdoor forklifts can operate near human-level performance, offering a viable path toward safer and more efficient construction logistics.

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Cite this paper

@article{huemer2025adapt,
  title  = {ADAPT: An Autonomous Forklift for Construction Site Operation},
  author = {Johannes Huemer and Markus Murschitz and Matthias Schörghuber and Lukas Reisinger and Thomas Kadiofsky and Christoph Weidinger and Mario Niedermeyer and Benedikt Widy and Marcel Zeilinger and Csaba Beleznai and Tobias Glück and Andreas Kugi and Patrik Zips},
  year   = {2025},
  eprint = {2503.14331},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2503.14331v3}
}

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