ADAPT: An Autonomous Forklift for Construction Site Operation
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Abstract (arXiv)
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.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 23 of its 102 references that are in the map. First posted on arXiv 18 Mar 2025.
Builds on
23 of 102 references.
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11 more
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Built on by
Citing papers per year: 2025: 1; 2026: 2.
3 papers.
- 2025Lang2Lift: A Language-Guided Autonomous Forklift System for Outdoor Industrial Pallet Handlingcited by 0
- 2026PIRATR: Parametric Object Inference for Robotic Applications with Transformers in 3D Point Cloudscited by 0
- 2026Build on Priors: Vision--Language--Guided Neuro-Symbolic Imitation Learning for Data-Efficient Real-World Robot Manipulationcited by 0
- 2026Build on Priors: Vision--Language--Guided Neuro-Symbolic Imitation Learning for Data-Efficient Real-World Robot Manipulation4 Apr 2026
- 2026PIRATR: Parametric Object Inference for Robotic Applications with Transformers in 3D Point Clouds5 Feb 2026
- 2025Lang2Lift: A Language-Guided Autonomous Forklift System for Outdoor Industrial Pallet Handling21 Aug 2025