Robot-Assisted Object Detection for Construction Automation: Data and Information-Driven Approach

Ilyas, Muhammad; Ying, Khaw Hui; Nithish, Muthuchamy Selvaraj; Xin, Jin Yu; Zhao, Xinge; Cheah, Chien Chern

doi:10.1109/tmech.2021.3100306

Cited by 38 publications

(9 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Despite claiming their robot to autonomously navigate from one point of the building to another, their experimentation does not provide enough proof to support that claim. Another approach using the BIM information, in this case for progress monitoring and quality assessment purposes, is the one of Ilyas et al (Muhammad et al, 2021). This information is used to generate a map to be used by the robot for navigation, also providing information regarding the position of the different elements to be inspected.…”

Section: Previous Workmentioning

confidence: 99%

Multiagent robotic systems and exploration algorithms: Applications for data collection in construction sites

Prieto,

Giakoumidis,

García de Soto

2024

Journal of Field Robotics

View full text Add to dashboard Cite

The construction industry has been notoriously slow to adopt new technology and embrace automation. This has resulted in lower efficiency and productivity compared to other industries where automation has been widely adopted. However, recent advancements in robotics and artificial intelligence offer a potential solution to this problem. In this study, a methodology is proposed to integrate multirobotic systems in construction projects with the aim of increasing efficiency and productivity. The proposed approach involves the use of multiple robot and human agents (HA) working collaboratively to complete a construction task. The methodology was tested through a case study that involved 3D digitization of a small, occluded space using two robots and one HA. The results show that integrating multiagent robotic systems (MARS) in construction can effectively overcome challenges and complete tasks efficiently. The implications of this study suggest that MARS could revolutionize the industry.

show abstract

Section: Previous Workmentioning

confidence: 99%

Multiagent robotic systems and exploration algorithms: Applications for data collection in construction sites

Prieto,

Giakoumidis,

García de Soto

2024

Journal of Field Robotics

View full text Add to dashboard Cite

show abstract

“…Besides identifying and interacting with objects, the system is imperative for identifying human workers from objects. Similar to this is robot-assisted object detection for construction robotics by Ilyas et al (2021). The robot system is equipped with perception sensors and intelligent algorithms and can help construction robotics identify construction materials, detect component installations and generate reports of their location and status.…”

Section: Construction Robotics and Human-robot Teams Research Areas T...mentioning

confidence: 99%

Research focus for construction robotics and human-robot teams towards resilience in construction: scientometric review

Onososen

Musonda

2022

JEDT

View full text Add to dashboard Cite

Purpose Rapid urbanisation and recent shock events have reiterated the need for resilient infrastructure, as seen in the pandemic. Yet, knowledge gaps in construction robotics and human–robot teams (HRTs) research limit maximising these emerging technologies’ potentials. This paper aims to review the state of the art of research in this area to identify future research directions in HRTs able to aid the resilience and responsiveness of the architecture, engineering and construction (AEC) sector. Design/methodology/approach A total of 71 peer-reviewed journal articles centred on robotics and HRTs were reviewed through a quantitative approach using scientometric techniques using Gephi and VOSviewer. Research focus deductions were made through bibliometric analysis and co-occurrence analysis of reviewed publications. Findings This study revealed sparse and small research output in this area, indicating immense research potential. Existing clusters signifying the need for further studies are on automation in construction, human–robot teaming, safety in robotics and robotic designs. Key publication outlets and construction robotics contribution towards the built environment’s resilience are discussed. Practical implications The identified gaps in the thematic areas illustrate priorities for future research focus. It raises awareness on human factors in collaborative robots and potential design needs for construction resilience. Originality/value Rapid urbanisation and recent shock events have reiterated the need for resilient infrastructure, as seen in the pandemic. Yet, knowledge gaps in construction robotics and HRTs research limit maximising these emerging technologies’ potentials. This paper aims to review the state of the art of research in this area to identify future research directions in HRTs able to aid the resilience and responsiveness of the AEC sector.

show abstract

“…The mobile robot autonomously navigates to a known target location and completes an indoor security task (Sun et al , 2022). The building information model (Ilyas et al , 2021) is a prior knowledge which gives specific spatial information to robot as target location. In above two researches, the target location is specific, the research contents focus on autonomous motion planning.…”

Section: Introductionmentioning

confidence: 99%

Path planning for robot search task using belief criteria decision-making

Zhao,

Liu,

et al. 2024

RIA

View full text Add to dashboard Cite

Purpose This study aims to realize efficient, fast and safe robot search task, the belief criteria decision-making approach is proposed to solve the object search task with an uncertain location. Design/methodology/approach The study formulates the robot search task as a partially observable Markov decision process, uses the semantic information to evaluate the belief state and designs the belief criteria decision-making approach. A cost function considering a trade-off among belief state, path length and movement effort is modelled to select the next best location in path planning. Findings The semantic information is successfully modelled and propagated, which can represent the belief of finding object. The belief criteria decision-making (BCDM) approach is evaluated in both Gazebo simulation platform and physical experiments. Compared to greedy, uniform and random methods, the performance index of path length and execution time is superior by BCDM approach. Originality/value The prior knowledge of robot working environment, especially semantic information, can be used for path planning to achieve efficient task execution in path length and execution time. The modelling and updating of environment information can lead a promising research topic to realize a more intelligent decision-making method for object search task.

show abstract

Robot-Assisted Object Detection for Construction Automation: Data and Information-Driven Approach

Abstract: Robot-assisted object detection for construction automation : data and information-driven approach. IEEE/ASME Transactions On Mechatronics.

Cited by 38 publications

References 34 publications

Multiagent robotic systems and exploration algorithms: Applications for data collection in construction sites

Multiagent robotic systems and exploration algorithms: Applications for data collection in construction sites

Research focus for construction robotics and human-robot teams towards resilience in construction: scientometric review

Path planning for robot search task using belief criteria decision-making

Contact Info

Product

Resources

About