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Auteurs principaux: Lin, Jia-Rui, Zhou, Shaojie, Pan, Peng, Cai, Ruijia, Chen, Gang
Format: Preprint
Publié: 2025
Sujets:
Accès en ligne:https://arxiv.org/abs/2505.04871
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author Lin, Jia-Rui
Zhou, Shaojie
Pan, Peng
Cai, Ruijia
Chen, Gang
author_facet Lin, Jia-Rui
Zhou, Shaojie
Pan, Peng
Cai, Ruijia
Chen, Gang
contents In concrete troweling for building construction, robots can significantly reduce workload and improve automation level. However, as a primary task of coverage path planning (CPP) for troweling, delimitating area of interest (AOI) in complex scenes is still challenging, especially for swing-arm robots with more complex working modes. Thus, this research proposes an algorithm to delimitate AOI for swing-arm troweling robot (SatAOI algorithm). By analyzing characteristics of the robot and obstacle maps, mathematical models and collision principles are established. On this basis, SatAOI algorithm achieves AOI delimitation by global search and collision detection. Experiments on different obstacle maps indicate that AOI can be effectively delimitated in scenes under different complexity, and the algorithm can fully consider the connectivity of obstacle maps. This research serves as a foundation for CPP algorithm and full process simulation of swing-arm troweling robots.
format Preprint
id arxiv_https___arxiv_org_abs_2505_04871
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle SatAOI: Delimitating Area of Interest for Swing-Arm Troweling Robot for Construction
Lin, Jia-Rui
Zhou, Shaojie
Pan, Peng
Cai, Ruijia
Chen, Gang
Robotics
In concrete troweling for building construction, robots can significantly reduce workload and improve automation level. However, as a primary task of coverage path planning (CPP) for troweling, delimitating area of interest (AOI) in complex scenes is still challenging, especially for swing-arm robots with more complex working modes. Thus, this research proposes an algorithm to delimitate AOI for swing-arm troweling robot (SatAOI algorithm). By analyzing characteristics of the robot and obstacle maps, mathematical models and collision principles are established. On this basis, SatAOI algorithm achieves AOI delimitation by global search and collision detection. Experiments on different obstacle maps indicate that AOI can be effectively delimitated in scenes under different complexity, and the algorithm can fully consider the connectivity of obstacle maps. This research serves as a foundation for CPP algorithm and full process simulation of swing-arm troweling robots.
title SatAOI: Delimitating Area of Interest for Swing-Arm Troweling Robot for Construction
topic Robotics
url https://arxiv.org/abs/2505.04871