Construction Of Robot Research Articles

Transforming fire protection: AI's evolving role in proactive and reactive applications

Abstract. This paper comprehensively reviews the applications of artificial intelligence (AI) in the field of fire protection. It traces the historical development of AI, from its origins in the 1930s and 1940s to its current state, focusing on major milestones and algorithms that have shaped the field. The paper discusses the evolution of AI, particularly in terms of machine learning, deep learning, and the emergence of various models such as deep neural networks (DNNs), transformer models, and graph neural networks (GNNs). The application of AI in fire protection is explored in two primary categories: proactive and reactive applications. Proactive applications encompass AI's role in decision-making, construction, and operation, including the use of machine learning for environmental analysis, building information modelling (BIM) for design optimization, 3D printing and intelligent robots in construction, and intelligent fire facility management. Reactive applications focus on early fire detection and monitoring, especially in forests, utilizing terrestrial, aerial, and satellite systems equipped with advanced sensors and deep learning techniques. This paper highlights the significant contributions of AI in mitigating fire risks, improving fire detection and response, and enhancing the safety and efficiency of fire protection systems.

Optimizing Construction Management and Workflow Integration through Autonomous Robotics for Enhanced Productivity Safety and Precision on Modern Construction Sites

The construction industry is experiencing a technological transformation with the integration of robotics, fundamentally altering traditional construction management and process design. This review explores the role of construction robots in enhancing productivity, safety, and efficiency on construction sites. It examines the various types of robots used, such as bricklaying and welding robots, and analyzes their functions and real-world applications. The paper also addresses the design of workflows and processes around robots, highlighting the challenges and strategies involved in adapting construction projects to a robot-centric approach. Additionally, the impact of robotics on construction management, including shifts in roles, cost efficiency, and collaboration between humans and robots, is thoroughly explored. The review concludes by identifying future trends, challenges, and opportunities in the field of construction robotics, along with relevant policy and regulatory considerations. This paper aims to provide insights into how construction management must evolve to successfully integrate robots, leading to a more efficient, cost effective, and safe construction environment.

Numerical and experimental study on reinforced 3DCP walls filled with light-weight concrete

This paper explores the structural viability of 3DCP as a novel additive manufacturing method in the construction industry, focusing on its integration and standardization challenges due to its emerging nature. With the construction industry's increasing interest in innovative materials and robotic construction, 3DCP's unique characteristics necessitate thorough investigation to understand its potential fully. This study aimed to assess the structural capacity of 3DCP walls, employing flexural tests on samples filled with lightweight concrete containing EPS, and comparing the outcomes with those of traditionally cast concrete. Through a comprehensive approach that combines experimental work with numerical analysis, this study intended to calibrate the material's properties based on small-scale tests to inform the design of larger structures. Macro and micro-scale numerical modeling methods were investigated for the analysis of 3DCP. The findings revealed that the inherent strength of 3DCP significantly depends on the material's composition and quality. Moreover, it was observed that the structural integrity of 3DCP walls was somewhat inferior to that of fully cast counterparts. However, a strong correlation between the numerical simulations and experimental data underscores the value of this research. By calibrating 3DCP's properties from small-scale experiments, the study provides a foundational basis for designing larger structures with enhanced reliability. Both numerical methods demonstrate high accuracy for the analysis of 3DCP and can be adopted for the analysis of larger structures.

Efficient 3D robotic mapping and navigation method in complex construction environments

AbstractRecent advancements in construction robotics have significantly transformed the construction industry by delivering safer and more efficient solutions for handling complex and hazardous tasks. Despite these innovations, ensuring safe robotic navigation in intricate indoor construction environments, such as attics, remains a significant challenge. This study introduces a robust 3‐dimensional (3D) robotic mapping and navigation method specifically tailored for these environments. Utilizing light detection and ranging, simultaneous localization and mapping, and neural networks, this method generates precise 3D maps. It also combines grid‐based pathfinding with deep reinforcement learning to enhance navigation and obstacle avoidance in dynamic and complex construction settings. An evaluation conducted in a simulated attic environment—characterized by various truss structures and continuously changing obstacles—affirms the method's efficacy. Compared to established benchmarks, this method not only achieves over 95% mapping accuracy but also improves navigation accuracy by 10% and boosts both efficiency and safety margins by over 30%.

In‐Pipe Maintenance Robot Using Spray‐In‐Place Pipe Technique for Long‐Distance and Complex Pipe Environment

ABSTRACTConventional pipe rehabilitation technologies are not the most sustainable solution for the utility industry because of various drawbacks, such as time consumption, disturbance to operations, society, and traffic, and the production of waste material. However, aged underground metal pipes are affected by natural forces. Trenchless rehabilitation technologies have been introduced for the treatment and renovation of aged pipes to ensure that utilities are safe and durable from an economic perspective. This paper proposes a portable and automatic robotic solution for a trenchless spray‐in‐place pipe approach for small underground pipelines. This approach shortens the duration of the rehabilitation operation from approximately a week to < 5 h. The robot delivered and monitored a protective well‐mixed urethane coating with plural components accurately using rotary mixing and spraying with a low‐pressure and safer configuration (< 0.8 MPa). The robot exhibited superior capacities in complicated pipe environments for turning into 90° elbows and 6‐in. (150 mm), 8‐in. (200 mm), and 10‐in. (250 mm) pipelines. An automated robot was deployed and rehabilitated at various underground and on‐ground pipe sites. The spray performance was validated using tensile tests. This robot can be applied to any pipeline system and can be developed for other in‐pipe robotic construction and renovation approaches.

Virtual Prototype Construction and Motion Simulation of Submarine Cable Outer Wall Inspection Robot Based on CAD and Reinforcement Learning

Virtual Prototype Construction and Motion Simulation of Submarine Cable Outer Wall Inspection Robot Based on CAD and Reinforcement Learning

Competencies for Human-Robot Collaboration in the Construction Industry – Academia’s Perspective

ABSTRACT This paper investigates the perceptions of Construction Engineering and Management instructors regarding the competencies for Human-Robot Collaboration (HRC) in construction to determine knowledge areas, skills, and abilities prioritized for facilitating effective collaboration between humans and robots in the industry. A two-round Delphi study was employed to evaluate the perceptions of construction instructors regarding HRC competencies. This study’s findings revealed that human-robot collaboration knowledge areas prioritized by the instructors include HRC ethics and regulation, robot anatomy and technical specifications, construction robot applications, sensors, and task planning. The instructors prioritized skills such as task planning, application of machine learning algorithms, safety management, human-robot interface proficiency, and effective communication. HRC abilities prioritized include decision-making, continuous learning, critical thinking, attention to detail, analytical aptitude, and adaptability. This research established the competencies prioritized by the instructors for implementing HRC in the construction industry and recommended future research directions.

Multi-scalar robotic fabrication system for on-site press gluing in multi-storey timber buildings

The amount of timber construction has increased significantly in recent decades due to the development of digital processing technologies in prefabrication. However, on site, timber components are still commonly assembled manually and connected with low performance joint types. This paper presents a multi-storey timber building system with a co-designed heterogeneous multi-scalar robotic construction system, consisting of a clamping device, an industrial robotic arm, and an automated crane, for the automation of on-site timber construction. By integrating construction features into the building material, the different robotic entities can work together to assemble a point-supported quasi-monolithic timber panel of theoretically unlimited dimensions with high precision.

Automating historical centering-minimizing masonry vaulting strategies: Applications to cooperative robotic construction

This paper investigates the feasibility of adapting ancient historical construction techniques to cooperative robotic assembly methods to minimize centering requirements in masonry vaults. First, an overview of seven historical techniques is presented. Next, a classification framework is introduced to evaluate the automation potential of these methods, identifying the rib network as the most promising candidate. This is followed by two computational case studies on the cooperative robotic construction of planar masonry arches and multi-arch rib networks. These studies evaluated the impact of robotic reachability and support payload on the feasibility of centering-free construction. A conclusion based only on these simulation results is that high-payload fixed robots, in comparison to medium-payload mobile setups, allow for the construction of larger and more complex rib structures. This research is of relevance to architects and engineers interested in using a cooperative robotic fabrication framework to reduce centering in masonry vault construction.

Cost Assessment Framework for Construction Robots: Comparative Study of Robotic and Traditional Construction

Cost Assessment Framework for Construction Robots: Comparative Study of Robotic and Traditional Construction

Working space planning for wheeled robot overturning stability

Abstract Mobile manipulators have been widely used in the field of building construction. Typical features of construction robots include crossing various rugged terrains in construction sites, carrying heavy payloads, and performing tasks in a large workspace, which may lead to unstable posture or overturning. The tipping of the mobile manipulator, especially when carrying a payload, will cause danger to the surrounding environment and staff, leading to the termination of the task. The purpose of this study is to establish a real-time tipping prediction system, which can be used to avoid tipping of mobile manipulators. By employing the CAD model of the robot and parameters such as the center of gravity and direction, we can ascertain and assess the instability of the robot and the overturning algorithm, thus providing early warning and averting any potential danger.

The Integration of Artificial Intelligence in Architectural Visualization Enhances Augmented Realism and Interactivity

The construction industry is an important part of the national economic market of various countries; since 2013, the construction industry's added value in the gross domestic product has been more than 6%, reaching 6.89% in 2022, and is a pillar industry of the national economy. Intelligent construction is the realistic demand to promote the high-quality development of China's construction industry. It is the key focus of transforming and upgrading the traditional construction industry to information, digital, and intelligent. As a new production factor, construction robots have become the key to promoting intelligent construction. Under the guidance of various national and industry policies, thanks to China's huge construction market volume and rich application scenarios, many innovative and entrepreneurial entities have entered the field of construction robots. Architectural visualization is a crucial aspect of architectural design and communication. With the development of science and technology, artificial intelligence (AI) technology is increasingly becoming an essential tool for architectural visualization and communication. The emergence of AI technology has provided architects with more flexible and creative ways to present design ideas. All along, designers who love architecture have been passionate about exploring better solutions for architecture, but there is never an optimal solution for architectural design; AI is the fire of the future era; it brings us more opportunities but also forces us to face new challenges from the future.

Sustainable Impact of Stance Attribution Design Cues for Robots on Human–Robot Relationships—Evidence from the ERSP

With the development of large language model technologies, the capability of social robots to interact emotionally with users has been steadily increasing. However, the existing research insufficiently examines the influence of robot stance attribution design cues on the construction of users’ mental models and their effects on human–robot interaction (HRI). This study innovatively combines mental models with the associative–propositional evaluation (APE) model, unveiling the impact of the stance attribution explanations of this design cue on the construction of user mental models and the interaction between the two types of mental models through EEG experiments and survey investigations. The results found that under the influence of intentional stance explanations (compared to design stance explanations), participants displayed higher error rates, higher θ- and β-band Event-Related Spectral Perturbations (ERSPs), and phase-locking value (PLV). Intentional stance explanations trigger a primarily associatively based mental model of users towards robots, which conflicts with the propositionally based mental models of individuals. Users might adjust or “correct” their immediate reactions caused by stance attribution explanations after logical analysis. This study reveals that stance attribution interpretation can significantly affect users’ mental model construction of robots, which provides a new theoretical framework for exploring human interaction with non-human agents and provides theoretical support for the sustainable development of human–robot relations. It also provides new ideas for designing robots that are more humane and can better interact with human users.

Enhancing construction management outcomes through the mitigation of robotics implementation barriers: A sustainable practice model

Incorporating technology into construction projects is highly important to achieve success. One of the critical technologies is robotics, but it faces significant barriers in terms of implementing it in the construction sector. Existing research focuses on the benefits of robotics in terms of construction management. Besides this, there is limited known study that simultaneously focuses on overcoming the barriers and their impact on success in construction projects. This research was aimed at evaluating the barriers faced in the implementation of robotics in construction and determining their impact on success. A quantitative research design was followed, starting with the identification of possible challenges from the literature, performing the pilot survey, conducting the exploratory factor analysis (EFA), and performing structural equation modeling (SEM). The results produced a structural model involving barriers and their relation to construction success with a significant positive relation value of B = 0.87. Positive implications are formulated in relation to managerial and theoretical expectations of future robotics implementation in construction projects.

From muscular to dexterous: A systematic review to understand the robotic taxonomy in construction and effectiveness

AbstractThis work presents an investigation of robotic technologies' effectiveness in construction activities. Sixty‐four highly relevant publications were identified from the database. By systematically reviewing the publications, the secondary data that are of interest to the review theme were retrieved and further evaluated. It is found that robotic technologies for automated construction is a growing field, where the taxonomy of robot was reflected in a diversified manner in the existing studies, ranging from the muscular guy—robotic manipulator—to the dexterous ones—unmanned aerial vehicle, autonomous mobile robot, automated guided vehicle, autonomous construction machinery and quadruped robot. In addition, the existing studies have provided substantial evidence to reveal the robotic technologies' effectiveness against traditional human methods in construction scenarios, and the measures for effectiveness consisted of productivity, precision, and success rate. With the evidence, it seems that the construction sector could benefit from robotic technologies to achieve intelligent workflows. Furthermore, based on the existing knowledge foundation in the current literature, a theoretical framework for future research direction is proposed. The framework envisages the integration of large models with construction robots to address operational inefficiencies, reduce costs, and simplify management.

Research Review and Future Directions of Key Technologies for Welding Robots in the Construction Industry

The rapid development of the construction industry has highlighted the urgent need for enhanced construction efficiency and safety, propelling the development of construction robots to ensure sustainable and intelligent industry advancement. Welding robots, in particular, hold significant promise for application in steel structure construction. However, harsh construction environments, variable construction structures, and complex construction conditions present critical technical challenges for weld position, path, and quality for welding robots. This paper aims to provide a focused review of the key technical difficulties faced by welding robots in the construction industry, starting from the progress in research and applications. The review identifies the current state of welding robot technology, the technical bottlenecks encountered, and the potential solutions to these challenges, offering valuable insights for the research and development of construction robots.

An interactive simulation of control and coordination strategies for swarms of autonomous construction robots

An interactive simulation of control and coordination strategies for swarms of autonomous construction robots

Unified recursive kinematics and statics modeling of a redundantly actuated series-parallel manipulator with high load/mass ratio

Construction robots with mobile systems are an integral part of automatic building processes. However, with the vigorous development of prefabricated buildings, traditional manipulators have progressively failed to satisfy the requirements of handling heavy materials on construction sites. Thus, this paper proposes a redundantly actuated series-parallel manipulator (RAS-PM). To explore the feasibility of applying the manipulator in construction tasks, this paper establishes the unified recursive kinematics and statics of the manipulator and verifies the validity and reliability of the theoretical modeling method through comprehensive numerical results. The prototype of the manipulator is developed and installed on a bionic hexapod construction robot. The test results demonstrate that the manipulator exhibits an excellent load/mass ratio in non-redundant actuation mode, and its load-carrying capacity can be further enhanced with the optimized force/position hybrid actuation. In the on-site test, the robot can freely switch between modes to handle horizontal and vertical states of materials, such as curtain walls and large panels, thereby contributing to modern prefabricated construction.

Challenges of Robotic Technology in Sustainable Construction Practice

This review discusses new technologies in the construction industry, such as digitalization, automation, and robotization, which have an impact on improving sustainable construction in the digital transformation in the era of Industry 4.0. This review focuses specifically on the impact of robotic technology on the triad of sustainable construction: economy, environment, and society. Current trends in the construction industry related to common data environments (CDEs), building information modeling (BIM), construction robots (CRs), and bricklaying robots (BRs) are highlighted. Robotics technology used throughout the construction industry in a sustainable construction context is presented, including bricklaying, plastering, painting, welding, prefabrication, and material handling. New trends in robotics technology with respect to robotic bricklaying are presented, and the first mobile robotic bricklaying system (RBS) in Poland, which was designed, modeled, simulated, and built from scratch, is distinguished. The RBS was tested under laboratory conditions and verified on the construction site. Included are the main factors that make it impossible to spread robotic technology on construction sites, and furthermore, many solutions are proposed to problems associated with the robotic transformation. The discussed robotic technology is not limited only to a purely technical approach but takes into account challenges corresponding to the circular economy.

Two-stage task allocation for multiple construction robots using an improved genetic algorithm

The construction industry is facing serious challenges, such as labor shortage and safety hazards. Construction robots can perform dangerous and repetitive tasks instead of workers. However, complex construction tasks require multi-robot collaboration, which needs efficient task allocation. This paper describes a two-stage task allocation method using an improved Genetic Algorithm (GA) for multiple construction robots. First, a construction task decomposition and grouping method under construction constraints is established, using a steel structure as example. Second, a Multi-Robot Construction Task Allocation (MRCTA) model is developed by modeling construction robots and tasks. Third, the MRCTA problem is divided into two stages, i.e., determining the optimal construction robot group for each task and the best task sequence for each robot group. Finally, a simulated experiment was designed and conducted. The results show that the method can efficiently find optimal solutions and the improved GA can enhance the diversity to achieve well-adapted solutions.