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Abdelkhalek, S; Zayed, T; Eltoukhy, A E E (2025) Multifaceted optimization for bridge inspection process. Journal of Construction Engineering and Management, 151(5).
Afolabi, A; Yusuf, A; Akanmu, A (2025) Effect of a passive shoulder-support exoskeleton on muscle activity, range of motion, discomfort, and exertion during painting tasks. Journal of Construction Engineering and Management, 151(5).
Ahmed, K; Leung, M Y; Yang, W; Manu, P (2025) Moderating effects of coping behaviors on stressor-stress relationships of ethnic minority construction workers. Journal of Construction Engineering and Management, 151(5).
Bhattacharjee, K; Bugalia, N; Mahalingam, A (2025) Differences in pathways to resilient safety culture for construction projects of different sizes. Journal of Construction Engineering and Management, 151(5).
Chen, Z; Li, T; Qin, L; Jiang, Y (2025) Vision-guided autonomous block loading in a dual-robot collaborative handling framework. Journal of Construction Engineering and Management, 151(5).
- Type: Journal Article
- Keywords: block loading; coarse-to-fine localization; computer vision; material handling
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/JCEMD4.COENG-15847
- Abstract:
The construction industry is rapidly evolving and increasingly requires automation in material handling. While robotic solutions have been introduced for transportation and unloading, the loading phase remains largely dependent on manual labor. Blocks, a fundamental building material in construction, lack automated loading solutions due to the unstructured nature of construction sites and the need for high precision. This paper presents a vision-based collaborative robotic system designed for automated block loading. The proposed system integrates a novel three-stage visual localization pipeline that employs a coarse-to-fine hierarchical mechanism for object localization. Stage I utilizes deep vision networks to detect and localize the target block, enabling autonomous robotic grasping. Stage II addresses grasping inaccuracies using binocular stereo-vision models to measure the in-hand block's pose. Advanced deep learning techniques handle detection complexities and uncertainties, while traditional model-based methods ensure precision. Stage III is used for autonomous placement, employing marker-based metrology to quickly establish a local reference frame, thus mitigating cumulative stacking errors. A highly automated pipeline for generating large-scale, labeled simulation datasets is also developed to train neural networks. Laboratory and field experiments demonstrate the system's effectiveness, achieving a 95.8% success rate and continuous stacking accuracy of 2.95 mm. This study contributes to the existing body of knowledge by introducing a novel robotic solution for autonomous block loading, offering a three-stage visual localization approach that ensures high success rates and precision. Furthermore, this study advances the understanding of the accuracy assurance mechanism. It demonstrates the effectiveness of multirobot collaboration and visual localization algorithms in construction automation.
Cuervo, J C and Pheng, L S (2003) Significance of location factors for Singapore transnational construction corporations. Engineering, Construction and Architectural Management, 10(5), 342–53.
Fares, A; Elazouni, A; Al-Alawi, M (2025) Using game theory to negotiate win-win payment terms between contractors and subcontractors. Journal of Construction Engineering and Management, 151(5).
Fernández, A I; Jarufe, J; Segarra, P; Cavieres, P (2025) Management of construction planning process in massive underground mining by integrating LPS and cit through action research. Journal of Construction Engineering and Management, 151(5).
Hong, W T; Whyte, J; Xue, J (2025) A natural language processing-driven framework for policymaking in infrastructure development. Journal of Construction Engineering and Management, 151(5).
Lee, D; Han, K (2025) Autonomous navigation and positioning of a real-time and automated mobile robotic welding system. Journal of Construction Engineering and Management, 151(5).
Sciulli, G; Rizzo, P; Kurlander, J; Brozik, B (2025) A comparative analysis of three methodological frameworks for bridge asset management. Journal of Construction Engineering and Management, 151(5).
Shehadeh, A; Alshboul, O (2025) Game theory integration in construction management: A comprehensive approach to cost, risk, and coordination under uncertainty. Journal of Construction Engineering and Management, 151(5).
Thiruvenghadam, T S; Prakash, A (2025) Emerging paradigms and practices in construction equipment management. Journal of Construction Engineering and Management, 151(5).
Umair, M; Seo, J; Luo, Y; Ahn, C R (2025) Investigating the impact of virtual reality accident experience on construction workers' risk habituation through individual behaviors. Journal of Construction Engineering and Management, 151(5).
Uthai, T; Zhou, T; Ye, Y; You, H; Du, J (2025) Haptics-based robot teleoperation for soft object manipulation. Journal of Construction Engineering and Management, 151(5).
Wang, M; Yao, G; Yang, Y; Li, R; Deng, R (2025) A decision support tool for dust prevention and control in construction. Journal of Construction Engineering and Management, 151(5).
Xia, N; Ding, S; Zhai, F; Xia, M (2025) Sharing psychological safety climate at the group level among construction workers: The roles of group identification and interactional justice. Journal of Construction Engineering and Management, 151(5).
Yllmaz, M; Dede, T (2025) Optimizing multiobjective time-cost-quality problems in construction projects: Efficacy of strength Pareto-based rao algorithms. Journal of Construction Engineering and Management, 151(5).
Zhou, Y; Liu, J; Pu, X; Ding, Y (2025) Signaling game analysis of transfer mechanisms of PPP projects: Considering investors' moral hazard and adverse selection behavior. Journal of Construction Engineering and Management, 151(5).