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GPU-accelerated collision-free path planning for multi-axis robots in construction automation
(2025)
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.
3D printing has gained significant popularity in construction in recent years, along with a growing focus on earth-based materials. These materials must adhere to certain principles to ensure printability and extrudability, allowing for good consistency during the printing process. This would need extra water, resulting in a wet mixture that could decrease the production printing rate per day and limit overhang structures due to the wet materials. One challenge facing these materials is their slow drying process, especially in low temperatures and humid climates. However, the strength and stiffness of these materials are gained by time when water evaporates. Given the limited studies on the drying process during 3D printing, this research aims to explore the structural stability of maximum support-free overhangs using a custom-designed heating system based on Active Hot Air Drying System (HADS) that mimics sun drying. This system accelerates and aids the drying process of the layers, ensuring greater structural stability without deformation. According to the results, the contentious heating system increased layer stability by reaching more layers at once. The maximum overhang reached was an angle of 50 degrees before failure at 60 degrees. In conclusion, the research highlighted and promoted the use of earth-based materials and offered some solutions to ensure that printed buildings could be dried fast. This is a solution to establish earth as a reliable material in structures in a contemporary way with the use of 3D printing.
Accurate spatial localization is critical in the construction industry, indoor robotics, and other applications involving actor movement within buildings. This paper introduces a combined software and hardware framework designed to evaluate indoor localization systems leveraging optical tracking integrated with a ROS communication system. It supports recording location data, aligning trajectories and evaluating the recorded samples against the ground truth allowing for real world comparison within a custom setup. While it is designed to evaluate any localization system, a presented case study compares two established SLAM algorithms regarding their suitability for an AEC application.
This study explores the "Artificial Ossification" algorithm's application in real-world structures, inspired by human bone formation. It uses agents mimicking bone-building and degrading cells to iteratively optimize structures for equilibrium through the Finite Element Method. The research proposes a 3D printing pen method for material addition or removal, mirroring natural bone adaptability and sustainability. Initial tests on 3D-printed models showed promising results, leading to more rigorous comparisons between conventional and algorithm-optimized structures. Findings confirm the algorithm's practicality for adaptive, optimized structural design, with potential applications in architecture, engineering, and beyond. The study also highlights the method's sustainability, repairability, and scalability, suggesting its relevance for future research in adaptive materials and design methods.
Since its first description in 1892, the adaptation of internal bone structure to changing loading conditions over time, known as Wolff 's Law, has inspired a wide range of research and imitation. This investigation presents a new bone-inspired algorithm, intended for the structural design of technical structures and capable of optimizing the shape and size of three-dimensional lattice structures. Unlike conventional structural optimization methods, it uses interacting artificial agents that closely follow the cellular behaviour of the biological blueprint. Agents iteratively move, alter cross-sections, and reposition axes in the latticework. The efficacy of the algorithm is tested and evaluated in two case studies. This agent-based approach lays the theoretical foundation for an implementation of adaptive structural building components and provides a tool for further research into the spatial aspects of natural ossification.