GPU-Accelerated Collision-Free Path Planning for Multi- Axis Robots in Construction Automation

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Publicat a:ISARC. Proceedings of the International Symposium on Automation and Robotics in Construction vol. 42 (2025), p. 421-428
Autor principal: Vukorep, Ilija
Altres autors: Starke, Rolf, Khajehee, Arastoo, Rogeau, Nicolas, Ikeda, Yasushi
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IAARC Publications
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Accés en línia:Citation/Abstract
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Resum:The Architecture, Engineering, and Construction (AEC) sector faces increasing pressure for higher production rates amidst a growing shortage of skilled labor, driving the demand for advanced robotic applications to enhance precision, efficiency, and adaptability in complex environments. This paper introduces a software setup designed to ensure collision-free movements for multi-axis robots in AEC scenarios. Our approach leverages the NVIDIA cuRobo framework's robust capabilities, seamlessly integrated with Grasshopper for Rhino 3D software (GH), a tool widely recognized for its versatility in parametric design. The integration of these technologies allows for the efficient online generation of optimal path movements, avoiding collisions even in highly intricate settings and changing environments. This is achieved in a remarkably short timeframe, enhancing productivity and reducing downtime. NVIDIAs framework's GPU-driven architecture paired with our GH parametric and controlling setup is a significant advancement, validated through a case study involving a complex, tree-like structure constructed from timber sticks. Using a six-axis robotic arm, the study demonstrates the system's capability to navigate and manipulate within congested spaces efficiently. With this enhanced automation workflow, new possibilities emerge for robotic applications, from industrial automation to sophisticated construction projects. Our GH software also allows visualization and exchange with URDF-models and better planning of collision logic, which was previously only possible with ROS and Nvidia Isaac technology.
Font:Advanced Technologies & Aerospace Database