Construction Of Robot Research Articles

Research on the Application of Construction Robots in the Context of Construction Industrialization

Based on the original construction technology, construction robots are realized by integrating industrial information technology, and construction robots are used to replace manual labor in completing construction projects. China’s research on construction robots is still in its early stages. Research efforts need to be increased in order to promote better applications of construction robots. To this end, by analyzing the application of modern construction robots, we conduct a comprehensive study on the development of construction robots to ensure that construction robots can be widely used in the future.

A framework for robotic excavation and dry stone construction using on-site materials.

Automated building processes that enable efficient in situ resource utilization can facilitate construction in remote locations while simultaneously offering a carbon-reducing alternative to commonplace building practices. Toward these ends, we present a robotic construction pipeline that is capable of planning and building freeform stone walls and landscapes from highly heterogeneous local materials using a robotic excavator equipped with a shovel and gripper. Our system learns from real and simulated data to facilitate the online detection and segmentation of stone instances in spatial maps, enabling robotic grasping and textured 3D scanning of individual stones and rubble elements. Given a limited inventory of these digitized stones, our geometric planning algorithm uses a combination of constrained registration and signed-distance-field classification to determine how these should be positioned toward the formation of stable and explicitly shaped structures. We present a holistic approach for the robotic manipulation of complex objects toward dry stone construction and use the same hardware and mapping to facilitate autonomous terrain-shaping on a single construction site. Our process is demonstrated with the construction of a freestanding stone wall (10 meters by 1.7 meters by 4 meters) and a permanent retaining wall (65.5 meters by 1.8 meters by 6 meters) that is integrated with robotically contoured terraces (665 square meters). The work illustrates the potential of autonomous heavy construction vehicles to build adaptively with highly irregular, abundant, and sustainable materials that require little to no transportation and preprocessing.

Integrating early assessment of robotic constructability into design optimization of a standalone classroom

Multi-objective optimization can enhance design quality through performance simulation. However, ease or efficiency of construction is also important, and optimization may lead to difficult-to-build designs. Early quantification of constructability would allow designers to balance performance and construction issues. While it is difficult to quantify all factors that influence constructability, robotic construction simulations offer rich datasets to compare potential outcomes. This paper integrates constructability knowledge into early-stage design and examines the impact on multi-objective optimization. It evaluates robotic material delivery systems in constructing a standalone classroom optimized for structural, daylighting, and energy goals. When considering robotic pick and place time, the optimized designs differ, offering the opportunity to change design directions based on construction knowledge. Broader implications also become observable, as incorporating robots with higher carrying capacities reduces the structural elements and embodied carbon of optimal designs. This paper thus demonstrates benefits of incorporating robotic constructability simulation into early design optimization.

Digital twin model construction of robot and multi-object under stacking environment for grasping planning

Object grasping is the basic function for robots to complete various tasks. However, it is still a hot and difficult problem to grasp object in multi-object stacking environment. A digital twin model construction method for robot grasping under multi-object stacking environment is proposed based on digital twin technology to realize multi-object grasping planning and virtual-real interaction. The robot digital twin model is constructed based on the requirements of the twin model, which includes the robot information model and information perception method. Then, the logical relationship between the virtual models of multi-object stacked objects is established based on the interactive relationship of stacked objects. The twin model of robot grasping under the multi-object stacking scene is built to realize the monitoring and visualization of the key elements of the physical entity of the robot based on ROS and Unity3D, and the interaction between the virtual model and the physical entity is realized to monitor the progress of robot grasping of multi-target objects. What’s more, the interaction relationship between objects is detected at the same time with an accuracy of 80 %. The experimental results verify the validity and reliability of the proposed method for establishing the digital twin model of robot grasping and the logical relation of the virtual model of objects.

Controlling the motion of gas-lubricated adhesive disks using multiple vibration sources.

Robots capable of generating adhesion forces that can achieve free movement in application environments while overcoming their own gravity are a subject of interest for researchers. A robot with controllable adhesion could be useful in many engineered systems. Materials processing equipment, robots that climb walls, and pick-and-place machines are some examples. However, most adhesion methods either require a large energy supply system or are limited by the properties of the contact plane. For example, electromagnetic adhesion requires a ferromagnetic surface and pneumatic adhesion requires a flat surface. Furthermore, nearly all existing approaches are only used to generate adhesion forces and often require additional mechanisms to remove the adhesive component from the surface. In this study, we aimed to develop a simpler method of adhering to a surface while simultaneously moving in directions parallel to the surface, using multiple vibration sources to generate normal adhesion and propulsion. To test our approach, we constructed circular and elliptical models and conducted experiments with various inputs and model parameters. Our results show that such a gas-lubricated adhesive disk could achieve adhesive rotation and displacement in the plane without requiring any auxiliary operating system. Using only vibration sources, we were able to generate the necessary adhesion and propulsion forces to achieve the desired motion of the robot. This work represents a step towards the construction of a small-sized tetherless robot that can overcome gravity and move freely in a general environment.

Revolution in the construction industry (2020-2023): how artificial intelligence is shaping the future of construction

The article highlights the current state of construction robotics equipped with artificial intelligence, which in turn actively develops and automates the construction industry. The foundations of this type of robotics were laid in the distant past, but specific prototypes of robots that were sporadically involved in the construction industry began to be actively developed in 2010-2015. The article presents the author's analysis of the report "Global Artificial Intelligence in Construction Market Analysis", published on the official electronic resource of the global analytical company Research Dive. The Report shows that since 2020, every fifth worker death per year has been recorded in the construction sector globally. Based on this report, the author also draws the main conclusions of the problems of integrating artificial intelligence into the construction industry. The article provides several specific examples of construction robots (IronBOT and TyBOT - a system of robots from Advanced Construction Robotics that can perform automated layout of reinforcing bars and their binding according to the main parameters (diameter of reinforcement, reinforcement pitch), construction software (Newmetrix Vinnie - a set of programs that, based on the analysis of photos and videos from construction, assist in predicting the health and safety of workers on construction sites, as well as predict deviations of construction from the design document), and construction software (Newmetrix Vinnie - a set of programs that, based on the analysis of photos and videos from construction sites, assist in predicting the health and safety of workers on construction sites, and predict deviations from the design document). Based on the material described above, the author summarises the current situation and identifies several current basic problems in the integration of artificial intelligence into the construction sector.

Towards Risk-Free Trustworthy Artificial Intelligence: Significance and Requirements

Given the tremendous potential and influence of artificial intelligence (AI) and algorithmic decision-making (DM), these systems have found wide-ranging applications across diverse fields, including education, business, healthcare industries, government, and justice sectors. While AI and DM offer significant benefits, they also carry the risk of unfavourable outcomes for users and society. As a result, ensuring the safety, reliability, and trustworthiness of these systems becomes crucial. This article aims to provide a comprehensive review of the synergy between AI and DM, focussing on the importance of trustworthiness. The review addresses the following four key questions, guiding readers towards a deeper understanding of this topic: (i) why do we need trustworthy AI? (ii) what are the requirements for trustworthy AI? In line with this second question, the key requirements that establish the trustworthiness of these systems have been explained, including explainability, accountability, robustness, fairness, acceptance of AI, privacy, accuracy, reproducibility, and human agency, and oversight. (iii) how can we have trustworthy data? and (iv) what are the priorities in terms of trustworthy requirements for challenging applications? Regarding this last question, six different applications have been discussed, including trustworthy AI in education, environmental science, 5G-based IoT networks, robotics for architecture, engineering and construction, financial technology, and healthcare. The review emphasises the need to address trustworthiness in AI systems before their deployment in order to achieve the AI goal for good. An example is provided that demonstrates how trustworthy AI can be employed to eliminate bias in human resources management systems. The insights and recommendations presented in this paper will serve as a valuable guide for AI researchers seeking to achieve trustworthiness in their applications.

Chasing millimeters: design, navigation and state estimation for precise in-flight marking on ceilings

Precise markings for drilling and assembly are crucial, laborious construction tasks. Aerial robots with suitable end-effectors are capable of markings at the millimeter scale. However, so far, they have only been demonstrated under laboratory conditions where rigid state estimation and navigation assumptions do not impede robustness and accuracy. This paper presents a complete aerial layouting system capable of precise markings on-site under realistic conditions. We use a compliant actuated end-effector on an omnidirectional flying base. Combining a two-stage factor-graph state estimator with a Riemannian Motion Policy-based navigation stack, we avoid the need for a globally consistent state estimate and increase robustness. The policy-based navigation is structured into individual behaviors in different state spaces. Through a comprehensive study, we show that the system creates highly precise markings at a relative precision of 1.5 mm and a global accuracy of 5–6 mm and discuss the results in the context of future construction robotics.

Development of Web-Based Teleoperation VOCAFE Service Robot

The design and implementation of a service robot that communicates effectively via the MQTT Protocol is presented in this research. This study focuses on creating a web-based application to control and monitor the movement of restaurant service robots in one of the university's cafes called VOCAFE. This research uses the MQTT communication protocol which allows smooth interaction between the robot and the operator. The design and construction of service robots, including their mechanical parts and communication systems, is described in the engineering section. The test results show the response time of the robot's navigation system, showing performance within a reasonable range. The conclusion highlights the importance of additional testing and research to improve the system. Overall, this research advances the creation of teleoperated restaurant service robots with reliable and effective communication using MQTT.

The Impact of Educational Robotics on Cognitive Outcomes in Primary Students: A Meta-Analysis of Recent Studies

<p style="margin-left: 21.3pt; text-align: justify;">In recent years, educational robotics has gained ground in educational policy around the world, and primary education is no exception. However, there has not yet been a thorough synthesis of methodologically appropriate empirical research on the effects of robotics upon cognitive performance among primary school students, which this paper attempted to do. Following literature screening, a total of eight studies published between 2018 and 2022 with a sample size of 567 children met inclusion criteria and were meta-analyzed. Resultantly, a medium aggregate effect size in favor of robotics experiments emerged (standardized mean difference of .641), which was significantly higher compared to non-robotics learning (p <.01). No between-study heterogeneity was detected. Subgroup analysis revealed a slightly larger overall effect for interventions on first- to third-graders rather than those in grades 4-6. Additionally, the analysis indicates that in order to enhance cognitive abilities in primary students, robotics interventions should be no longer than four weeks and involve robot construction. Based on the findings, implications, and suggestions are outlined for future research and practice.</p>

Designing Tomorrow: AI and the Future of Architectural Design Process

This essay explores the transformative role of Artificial Intelligence (AI) in the field of architecture, focusing on the impact on design innovation, production processes, as well as the ethical implications arising from inherent biases within these technologies. As AI becomes increasingly integrated into architectural practices, it offers the potential to revolutionize the discipline by enhancing efficiency, creativity, and sustainability. This investigation delves into the history and evolution of AI in architecture, tracing their journey from early computational design experiments to their current applications in generative design and robotic construction, which exemplify the shift towards more innovative and sustainable architectural practices. Furthermore, the essay highlights the involvement of the INNEN research team in integrating AI into academic and research activities within and besides the curriculum. It delves into the ways in which AI technologies are reshaping the boundaries of architectural design and construction, emphasizing on practical applications of AI in architectural design in education and professional work. This analysis uncovers the profound possibilities of AI in formulating groundbreaking design approaches and construction methods, underscoring research's role in propelling architectural thinking and practice forward through the use of technology.

Construction management in space: explore solution space of optimal schedule and cost estimate

Multi-planetary life is one of humanity's audacious dreams. A key challenge towards achieving such a space mission is the design and construction of space habitats, for instance, on Mars. This paper presents a virtual space construction decision framework (SCDF) prototype developed and tested to address the question: "How can space construction project partners make informed decisions and leverage new construction methods and cutting-edge technologies that are developed and transform the AEC terrestrial industry?" We consider six practical and theoretical points of departure reflecting knowledge and technology and their application towards developing SCDF: General Contractor Workflow; BIM; Generative Scheduling and Construction Schedule Optimization; Construction Robotics; 3D Printing; Virtual Reality (VR) and Visualization. SCDF development applied virtual design and construction (VDC) to model - simulate - optimize - visualize - validate a space construction project by exploring the solution space in the context of extra-terrestrial construction environments from concept design to construction completion in the virtual environment before any mission is launched. Results confirm that insights from terrestrial construction apply to extra-terrestrial construction and vice versa. These insights contribute to the six points of departure at three levels: 1. The SCDF; 2. Extensions to existing technology platforms; 3. New approaches and methods.

The State of the Art in Digital Construction of Clay Buildings: Reviews of Existing Practices and Recommendations for Future Development

Under the trend of digitization and global carbon reductions, clay construction has increasingly attracted attention due to advantages such as an excellent thermal performance, low carbon emissions, and high cost-effectiveness. In this article, an in-depth investigation is conducted into the potential, challenges, and future in the development of digital manufacturing technologies for clay architecture, especially 3D printing, robotic construction, and prefabrication systems. It is revealed through a review that digital clay construction is under rapid development and likely to provide a viable solution to achieving global carbon neutrality, which is conducive to addressing various regional issues. The key findings from this review are as follows. Firstly, as a flexible, precise, and low-carbon industrial solution, 3D printing lays a foundation for the extensive research on materials, equipment, and algorithm optimization. Secondly, the use of machine construction methods such as modern rammed earth technology and drone spraying is effective in improving efficiency and lowering costs. Lastly, the prefabricated building system shows its potential in renewing and developing the rammed earth architecture culture. These findings indicate a massive potential of digital clay construction to support sustainability efforts in the future.

Construction of micro-nano robots: living cells and functionalized biological cell membranes.

Micro-nano robots have emerged as a promising research field with vast potential applications in biomedicine. The motor is the key component of micro-nano robot research, and the design of the motor is crucial. Among the most commonly used motors are those derived from living cells such as bacteria with flagella, sperm, and algal cells. Additionally, scientists have developed numerous self-adaptive biomimetic motors with biological functions, primarily cell membrane functionalized micromotors. This novel type of motor exhibits remarkable performance in complex media. This paper provides a comprehensive review of the structure and performance of micro-nano robots that utilize living cells and functionalized biological cell membranes. We also discuss potential practical applications of these mirco-nano robots as well as potential challenges that may arise in future development.

Fault detection of harmonic reducer for construction robot based on adaptive state observer

AbstractThe traditional manual masonry technology of building wall has the problems of low construction efficiency and poor safety. The research of automatic masonry robot has become an urgent need. Harmonic reducer is the key component to ensure the construction robot to achieve good quality construction. This paper takes the “flexible assembly” of harmonic reducer as the research object. The system dynamics model is simplified and the reducer fault mathematical model is established. An adaptive state observer with greater design freedom is designed based on the fault model. This paper introduces adaptive threshold and performs parameter optimization. When no fault occurs in the system, the distance between the adaptive threshold and the residual is small and higher than the residual. When the system fails, the residual is higher than the adaptive threshold. This method solves the fault leakage alarm of the traditional detection method with a fixed threshold. The effectiveness of the fault detection scheme under constant fault and time‐varying fault is verified by simulation. The results show that the adaptive threshold method can effectively reduce the false alarm whether the reducer has a constant fault or a time‐varying fault, which shows that the fault detection scheme designed in this paper is effective.

Automatic high-level motion sequencing methods for enabling multi-tasking construction robots

Robots are expected to play an important role in future construction work. However, they are not yet widely adopted by the industry because it is difficult and expensive to program robots to conduct a variety of construction tasks. This paper presents a method for intuitively and flexibly teaching robots to perform various construction tasks through demonstrations. Robots are first programmed with basic skill primitives and then learn the sequencing of these primitive skills to perform different types of construction work under the guidance of human supervisors. The construction workflow and the interaction processes are enabled by a process-level digital twin system. Case studies with three assembly scenarios and a wooden frame construction experiment are used to present and verify the proposed method. The proposed approach enables automatic robot motion sequencing abilities through Learning from Demonstration and has the potential to enable the widespread adoption of robots on construction sites.

Design Optimization and Integrated Simulation Analysis of a Cable-Driven Ankle Rehabilitation Robot

Sprained ankles are the most commonly diagnosed injury seen by healthcare providers and are projected to account for up to 30% of sports medicine injuries, with lateral ankle sprain being the most common type. Ankle injuries necessarily involve motion assistance to regain mobility, but physiotherapists are typically able to provide rehabilitation only for one patient at each session. Numerous robotic rehabilitation strategies have been proposed in recent years; however, most of the designs have some limitations such as requiring the patient to sit or stand still. Hence, this study aims to develop a conceptual design and simulation of a compact wearable robot in aiding ankle motion for rehabilitation and training purposes. The cable-driven parallel architecture used in the construction of the cable-driven ankle rehabilitation robot allows for the exercise of the human ankle’s range of motion (ROM) to be maximized. The morphological chart analysis was created to explore the possible solutions to the design development for the ankle rehabilitation device, and the final design was decided using the Pugh method. A three-dimensional model of the proposed design was visualized in SolidWorks to analyze the inverse kinematics, trajectory simulation and cable length analysis. The feasibility of the ankle rehabilitation robot was examined against the simulation and was found to meet the requirements for performing effective ROM exercises for ankle rehabilitation. The proposed design could potentially be used for passive ankle joint rehabilitation exercise in specific ROM, particularly for bedridden patients.

Functional hydrogel-plastic hybrids inspired by the structural characteristics of mussels

Shellfish with rigid shells prevent damage to their delicate internal cores, and their soft bonding muscles drive the opening and closing of the shells. This synergism of rigid and soft materials provides shellfish with unique environmental adaptation. Inspired by the structural characteristics of mussels, a riveting layer was introduced into hydrogel-plastic hybrids for bonding hydrogel networks and plastic substrates. The bonding strength of the hydrogel on the polypropylene (PP) substrate was approximately 1.52 MPa, and the interface toughness reached 1450 J m−2. Furthermore, the integration of plastics and microscale hydrogels, as well as abscised or prefabricated hydrogels, could also be fabricated through the same process. By using this strategy, a hydrogel-plastic hybrid-based device with temperature responsiveness and scratch resistance was fabricated and could mimic the basic activities of mussels. This work improves the functional materials used in programmable engineering systems and could facilitate the construction of intelligent robots.

Enhancing construction robot learning for collaborative and long-horizon tasks using generative adversarial imitation learning

The development and deployment of robots on construction sites are integral to the industrialization of construction, known as Construction 4.0. Tele-operated and pre-programmed robots have enhanced construction efficiency and safety. However, their utilization on-site remains limited due to the need for expert remote control and the lack of adaptability in dynamic environments. Reinforcement learning (RL) has emerged as a promising solution, as RL-controlled robots possess inherent self-learning abilities to adapt to diverse situations. Nevertheless, manual design of RL reward functions for complex tasks poses challenges. To address this issue, inverse reinforcement learning (IRL) methods, such as Generative Adversarial Imitation Learning (GAIL), have been proposed to learn optimal actions through expert demonstration and self-exploration, without explicitly defined reward functions. In this study, we propose an innovative approach integrating GAIL and virtual reality (VR) integrated robot control approach to control robots for long-horizon collaborative construction tasks involving multiple sub-tasks. We employ VR expert demonstrations as input for GAIL training, enabling a team of robots, including an Unmanned Ground Vehicle (UGV) and two robot arms, to interact with the designed RL environment and perform tasks such as transporting, picking, and installing window panels. Handle long-horizon collaborative construction tasks (i.e., a long sequence of several sub-tasks performed by multiple robots). For evaluation, we compare the performance of our VR-GAIL model with a prevalent and robust RL baseline model, Proximal Policy Optimization (PPO). The results demonstrate that our reward-free VR-GAIL model achieves, on average, a 4.5% higher success rate than the PPO counterpart equipped with carefully designed reward functions across all three sub-tasks and their randomized variations. Furthermore, the performance gap between GAIL and PPO widens as the task difficulty increases. These findings indicate that our approach effectively enhances RL agent performance in tackling complex construction tasks while expediting development by eliminating reward function design requirements.

Multi-Camera-Based Human Activity Recognition for Human-Robot Collaboration in Construction.

As the use of construction robots continues to increase, ensuring safety and productivity while working alongside human workers becomes crucial. To prevent collisions, robots must recognize human behavior in close proximity. However, single, or RGB-depth cameras have limitations, such as detection failure, sensor malfunction, occlusions, unconstrained lighting, and motion blur. Therefore, this study proposes a multiple-camera approach for human activity recognition during human-robot collaborative activities in construction. The proposed approach employs a particle filter, to estimate the 3D human pose by fusing 2D joint locations extracted from multiple cameras and applies long short-term memory network (LSTM) to recognize ten activities associated with human and robot collaboration tasks in construction. The study compared the performance of human activity recognition models using one, two, three, and four cameras. Results showed that using multiple cameras enhances recognition performance, providing a more accurate and reliable means of identifying and differentiating between various activities. The results of this study are expected to contribute to the advancement of human activity recognition and utilization in human-robot collaboration in construction.