Large-scale construction projects can benefit from having a team of heterogeneous building robots operating autonomously and cooperatively on unstructured environments. In this work, we propose a flexible system architecture, MARSala, that allows teams of distributed mobile robots to construct motion support structures in large and unstructured environments using purely local interactions. The paper primarily focuses on the deliberative layer of the architecture which provides a means for formulating a construction project as a motion support structure construction problem. We implemented the architecture in simulation and demonstrated the benefits of such a formulation in two different construction scenarios operating in large unstructured environments.
more »
« less
This content will become publicly available on November 22, 2026
How to Build a Drum-Shaped House: A Replicative Experiment in Ancestral Architecture (Cusco, Peru)
Studies of late prehispanic architecture in the Andes have generally focused on rectangular and circular structures associated with the Inka Empire. Meanwhile, the architecture of non-Inka populations spans a remarkable diversity of non-orthogonal structures, implicating varied roof designs and construction techniques. This study addresses a gap in knowledge on architectural traditions through collaboration with the community of Huama (Lamay District). Specifically, the replicative construction of a wankar wasi (drum-shaped house) presented herein draws on traditional knowledge developed in Huama over the course of many generations. We also applied Mobile Laser Scanning to visualize and analyze the resultant structure. These data facilitate analogy between contemporary practices and the archaeological record to understand the materials, knowledge, and relationships engaged by prehispanic builders, with the objective of reconstructing local cooperation and resilience of under state occupation. Moreover, this research celebrates local heritage while illuminating the technological choices implicated in construction, past and present.
more »
« less
- Award ID(s):
- 2212652
- PAR ID:
- 10649984
- Publisher / Repository:
- Taylor & Francis
- Date Published:
- Journal Name:
- Ethnoarchaeology
- ISSN:
- 1944-2890
- Page Range / eLocation ID:
- 1 to 29
- Subject(s) / Keyword(s):
- Experimental archaeology labor construction technology traditional knowledge community-based research mobile laser scanning Inka Empire Andes
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Advances in computational technology provide opportunities to explore new methods to improve spatial abilities and the understanding of buildings in architecture education. The research employed BIMxAR, a Building Information Modeling-enabled AR educational tool with novel visualization features to support learning and understanding construction systems, materials configuration, and 3D section views of complex building structures. We validated the research through a test case based on a quasi-experimental research design, in which BIMxAR was used as an intervention. Two study groups were employed - non-AR and AR. The learning gain differences within and between the groups were not statistically significant, however, the AR group perceived significantly less workload and higher performance compared to the non-AR group. These findings suggest that the AR version is an easy, useful, and convenient learning tool.more » « less
-
Abstract Disasters provide an invaluable opportunity to evaluate contemporary design standards and construction practices; these evaluations have historically relied upon experts, which inherently limited the speed, scope and coverage of post-disaster reconnaissance. However, hybrid assessments that localize data collection and engage remote expertise offer a promising alternative, particularly in challenging contexts. This paper describes a multi-phase hybrid assessment conducting rapid assessments with wide coverage followed by detailed assessments of specific building subclasses following the 2021 M7.2 earthquake in Haiti, where security issues limited international participation. The rapid assessment classified and assigned global damage ratings to over 12,500 buildings using over 40 non-expert local data collectors to feed imagery to dozens of remote engineers. A detailed assessment protocol then conducted component-level evaluations of over 200 homes employing enhanced vernacular construction, identified via machine learning from nearly 40,000 acquired images. A second mobile application guided local data collectors through a systematic forensic documentation of 30 of these homes, providing remote engineers with essential implementation details. In total, this hybrid assessment underscored that performance in the 2021 earthquake fundamentally depended upon the type and consistency of the bracing scheme. The developed assessment tools and mobile apps have been shared as a demonstration of how a hybrid approach can be used for rapid and detailed assessments following major earthquakes in challenging contexts. More importantly, the open datasets generated continue to inform efforts to promote greater use of enhanced vernacular architecture as a multi-hazard resilient typology that can deliver life-safety in low-income countries.more » « less
-
This article highlights the absence of published paradigms hybridized by The Cuckoo Search (CS) and Stochastic Paint Optimizer (SPO) for optimizing truss structures using composite materials under natural frequency constraints. The article proposes a novel optimization algorithm called CSSPO for optimizing truss structures made of composite materials, known as fiber-reinforced polymer (FRP) composites, to address this gap. Optimization problems of truss structures under frequency constraints are recognized as challenging due to their non-linear and non-convex search spaces that contain numerous local optima. The proposed methodology produces high-quality optimal solutions with less computational effort than the original methods. The aim of this work is to compare the performance of carbon FRP (CFRP), glass FRP (GFRP), and steel using a novel hybrid algorithm to provide valuable insights and inform decision-making processes in material selection and design. Four benchmark structure trusses with natural frequency constraints were utilized to demonstrate the efficiency and robustness of the CSSPO. The numerical analysis findings indicate that the CSSPO outperforms the classical SPO and exhibits comparable or superior performance when compared to the SPO. The study highlights that implementing CFRP and GFRP composites in truss construction leads to a notable reduction in weight compared to using steel.more » « less
-
The `pre-train, prompt, predict' paradigm of large language models (LLMs) has achieved remarkable success in open-domain question answering (OD-QA). However, few works explore this paradigm in multi-document question answering (MD-QA), a task demanding a thorough understanding of the logical associations among the contents and structures of documents. To fill this crucial gap, we propose a Knowledge Graph Prompting (KGP) method to formulate the right context in prompting LLMs for MD-QA, which consists of a graph construction module and a graph traversal module. For graph construction, we create a knowledge graph (KG) over multiple documents with nodes symbolizing passages or document structures (e.g., pages/tables), and edges denoting the semantic/lexical similarity between passages or document structural relations. For graph traversal, we design an LLM-based graph traversal agent that navigates across nodes and gathers supporting passages assisting LLMs in MD-QA. The constructed graph serves as the global ruler that regulates the transitional space among passages and reduces retrieval latency. Concurrently, the graph traversal agent acts as a local navigator that gathers pertinent context to progressively approach the question and guarantee retrieval quality. Extensive experiments underscore the efficacy of KGP for MD-QA, signifying the potential of leveraging graphs in enhancing the prompt design and retrieval augmented generation for LLMs. Our code: https://github.com/YuWVandy/KG-LLM-MDQA.more » « less
An official website of the United States government
