Guanbo Chen, Beyza Kiper, Xuchu Xu, B. Sher, S. Ergan, Chen Feng
—Building envelope inspections are necessary to maintain buildings’ energy efficiency, but current solutions are expensive, time-consuming, and destructive. Furthermore, inspectors often face safety and accessibility issues. To mitigate these issues, we propose a holistic system, EASEEbot, consisting of robots to capture data and help retrofit and employ artificial intelligence to assist in data analysis. The robots including an unmanned aerial system (UAS) and ground-penetrating radar (GPR) accommodate data collection while the Robo- dog offers guidance to inspectors in retrofitting phase. The machine learning algorithm helps to analyze the captured data, identifies envelope issues, and generates a building’s digital twin to map identified defects spatially to buildings’ fac¸ades. The retrofit Robo-Dog uses the generated digital twin to project previously recorded defect imagery onto corresponding areas of the building’s envelope. It further guides workers to ensure the identified defective areas are addressed. EASEEbot offers non- destructive sensing, risk mitigation, and high-quality building envelope inspections.
{"title":"EASEEbot: A Robotic Envelope Assessment for Energy Efficiency","authors":"Guanbo Chen, Beyza Kiper, Xuchu Xu, B. Sher, S. Ergan, Chen Feng","doi":"10.22260/icra2022/0012","DOIUrl":"https://doi.org/10.22260/icra2022/0012","url":null,"abstract":"—Building envelope inspections are necessary to maintain buildings’ energy efficiency, but current solutions are expensive, time-consuming, and destructive. Furthermore, inspectors often face safety and accessibility issues. To mitigate these issues, we propose a holistic system, EASEEbot, consisting of robots to capture data and help retrofit and employ artificial intelligence to assist in data analysis. The robots including an unmanned aerial system (UAS) and ground-penetrating radar (GPR) accommodate data collection while the Robo- dog offers guidance to inspectors in retrofitting phase. The machine learning algorithm helps to analyze the captured data, identifies envelope issues, and generates a building’s digital twin to map identified defects spatially to buildings’ fac¸ades. The retrofit Robo-Dog uses the generated digital twin to project previously recorded defect imagery onto corresponding areas of the building’s envelope. It further guides workers to ensure the identified defective areas are addressed. EASEEbot offers non- destructive sensing, risk mitigation, and high-quality building envelope inspections.","PeriodicalId":179995,"journal":{"name":"Proceedings of the 1st Future of Construction Workshop at the International Conference on Robotics and Automation (ICRA 2022)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127435357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Kazemian, H. Gilbert, Yimin Zhu, M. Fiske, N. Alexandrov
Abstract - In this paper, we propose a teleoperated construction 3D printing technology, called TeleLayering, for planetary and terrestrial applications. The TeleLayering technology is enabled by effective multimodal control and monitoring systems and enhanced construction 3D printing robots to build or repair a variety of structures in extreme environments without the need for human presence on the jobsite. This paper presents a general description, main technical requirements, implementation challenges, and applications of this technology.
{"title":"TeleLayering: Teleoperated Construction 3D Printing Using Multimodal Feedback for Extraterrestrial and Terrestrial Construction","authors":"A. Kazemian, H. Gilbert, Yimin Zhu, M. Fiske, N. Alexandrov","doi":"10.22260/icra2022/0006","DOIUrl":"https://doi.org/10.22260/icra2022/0006","url":null,"abstract":" Abstract - In this paper, we propose a teleoperated construction 3D printing technology, called TeleLayering, for planetary and terrestrial applications. The TeleLayering technology is enabled by effective multimodal control and monitoring systems and enhanced construction 3D printing robots to build or repair a variety of structures in extreme environments without the need for human presence on the jobsite. This paper presents a general description, main technical requirements, implementation challenges, and applications of this technology.","PeriodicalId":179995,"journal":{"name":"Proceedings of the 1st Future of Construction Workshop at the International Conference on Robotics and Automation (ICRA 2022)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133078746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sean T. Bennett, P. Adamczyk, Fei Dai, D. Veeramani, Michael F. Wehner, Zhenhua Zhu
1 Abstract — The construction trade requires repetitive, physically demanding manual tasks which can over time pose severe risks for work-related musculoskeletal disorders (WMSDs) [1]. Exoskeletons and exosuits (collectively called “EXOs” in this work) have substantial potential to protect workers and to increase worker productivity by reducing exertion and fatigue. Despite these potential benefits, EXOs are uncommon in the construction industry. We present preliminary results from a pilot study investigating the knowledge gaps and barriers to EXO adoption. The overall objective of this work is to establish a foundational understanding of how EXOs can transform the future of construction trade work. The described work focuses on industry collaboration and field-based kinematic evaluation of three subjects performing a real-world construction task, removing wooden blocks from a steel-frame wall. We demonstrate the range of motion of the upper extremities of the subjects performing the task unassisted, followed by performing the task wearing two upper-extremity EXOs. This work is a presented in parallel with our separate study (evaluating the effects of a lower back EXO while dumping a gondola of refuse) also presented at this workshop. Our preliminary findings build a foundation of understanding of EXO-enabled construction tasks. This will foster EXO adoption and yield benefits including but not limited to improving the productivity of construction trades, reducing the risks of WMSDs and injuries of trade workers, broadening the workforce participation in construction trades, and extending the career life expectancy of existing trade workers.
{"title":"Upper extremity exoskeletons in construction, a field-based study","authors":"Sean T. Bennett, P. Adamczyk, Fei Dai, D. Veeramani, Michael F. Wehner, Zhenhua Zhu","doi":"10.22260/icra2022/0007","DOIUrl":"https://doi.org/10.22260/icra2022/0007","url":null,"abstract":"1 Abstract — The construction trade requires repetitive, physically demanding manual tasks which can over time pose severe risks for work-related musculoskeletal disorders (WMSDs) [1]. Exoskeletons and exosuits (collectively called “EXOs” in this work) have substantial potential to protect workers and to increase worker productivity by reducing exertion and fatigue. Despite these potential benefits, EXOs are uncommon in the construction industry. We present preliminary results from a pilot study investigating the knowledge gaps and barriers to EXO adoption. The overall objective of this work is to establish a foundational understanding of how EXOs can transform the future of construction trade work. The described work focuses on industry collaboration and field-based kinematic evaluation of three subjects performing a real-world construction task, removing wooden blocks from a steel-frame wall. We demonstrate the range of motion of the upper extremities of the subjects performing the task unassisted, followed by performing the task wearing two upper-extremity EXOs. This work is a presented in parallel with our separate study (evaluating the effects of a lower back EXO while dumping a gondola of refuse) also presented at this workshop. Our preliminary findings build a foundation of understanding of EXO-enabled construction tasks. This will foster EXO adoption and yield benefits including but not limited to improving the productivity of construction trades, reducing the risks of WMSDs and injuries of trade workers, broadening the workforce participation in construction trades, and extending the career life expectancy of existing trade workers.","PeriodicalId":179995,"journal":{"name":"Proceedings of the 1st Future of Construction Workshop at the International Conference on Robotics and Automation (ICRA 2022)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117000689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
— Construction sites typically involve a risky, dynamic, and challenging work environment. Despite numerous safety training programs and regulations, accidents still occur in construction sites, especially when working with construction robotics. To alleviate this problem in the most fundamental way, teleoperation that allows operators to work remotely has been studied. Teleoperated construction robots have the great potential to be used in various contexts for extreme and hazardous construction sites. Here, work conditions for human-robot interaction in construction differ from those in other structured and controlled environments like manufacturing factories, and thus there is a need for the associated studies. In this paper, we aim to measure and analyze the performance of human-robot interaction and the cognitive load of human operators in dynamic and challenging construction work environments (hazardous risks such as underground utility strikes and working under time constraints).
{"title":"The effect of challenging work environment on human-robot interaction and cognitive load during teleoperation: a case study of teleoperated excavator in a virtual experiment","authors":"Jin Sol Lee, Youngjib Ham","doi":"10.22260/icra2022/0017","DOIUrl":"https://doi.org/10.22260/icra2022/0017","url":null,"abstract":"— Construction sites typically involve a risky, dynamic, and challenging work environment. Despite numerous safety training programs and regulations, accidents still occur in construction sites, especially when working with construction robotics. To alleviate this problem in the most fundamental way, teleoperation that allows operators to work remotely has been studied. Teleoperated construction robots have the great potential to be used in various contexts for extreme and hazardous construction sites. Here, work conditions for human-robot interaction in construction differ from those in other structured and controlled environments like manufacturing factories, and thus there is a need for the associated studies. In this paper, we aim to measure and analyze the performance of human-robot interaction and the cognitive load of human operators in dynamic and challenging construction work environments (hazardous risks such as underground utility strikes and working under time constraints).","PeriodicalId":179995,"journal":{"name":"Proceedings of the 1st Future of Construction Workshop at the International Conference on Robotics and Automation (ICRA 2022)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132072407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Samuel Lensgraf, A. Sniffen, Alberto Quattrini Li, Devin J. Balkcom
—This paper presents StoneClaw, our custom- made free-floating autonomous underwater vehicle that plans for an efficient use of two complementary energy sources (battery and compressed air) and exploits self-correcting features on our designed manipulator, for con- structing structures with interlocking cement blocks.
{"title":"Towards the autonomous underwater construction of cement block structures with free-floating robots","authors":"Samuel Lensgraf, A. Sniffen, Alberto Quattrini Li, Devin J. Balkcom","doi":"10.22260/icra2022/0005","DOIUrl":"https://doi.org/10.22260/icra2022/0005","url":null,"abstract":"—This paper presents StoneClaw, our custom- made free-floating autonomous underwater vehicle that plans for an efficient use of two complementary energy sources (battery and compressed air) and exploits self-correcting features on our designed manipulator, for con- structing structures with interlocking cement blocks.","PeriodicalId":179995,"journal":{"name":"Proceedings of the 1st Future of Construction Workshop at the International Conference on Robotics and Automation (ICRA 2022)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121298559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
— Flaggers are a high-risk profession. They are always required to work closely with the open traffic lanes. Any distracted, speeding or intoxicated drivers might hit them, leading to their injuries and fatalities. From 1980 to 1992, a total of 54 fatalities involving flaggers in the construction industry have been reported. To protect flaggers and reduce their exposure to potential vehicular traffic, previous studies proposed and implemented the Automated Flagger Assistance Devices (AFADs). However, the AFADs have not been widely used in practice due to their costs. In addition to hiring a flagger to remotely operate an AFAD, the cost of an AFAD system alone ranges from $25,000 to $30,000 without the consideration of device maintenance. Instead of creating an assistance device, this paper proposed an automated flagging system (AFS) that can guide the traffic without the need for a flagger available on the site. The proposed system is composed of two modules: information capturing and decision-making. The information module is to monitor traffic conditions and retrieves useful information for the decision-making module to decide which sign (STOP or SLOW) to display in the LED panel. So far, a prototype was developed and tested in a laboratory environment. A vehicle detector was trained and integrated into the prototype. The laboratory test results indicated that the prototype could correctly show the STOP or SLOW sign based on the detection of simulated traffics.
{"title":"Vision-based Automated Flagging System in Construction","authors":"Wei Han, Zhenhua Zhu","doi":"10.22260/icra2022/0004","DOIUrl":"https://doi.org/10.22260/icra2022/0004","url":null,"abstract":"— Flaggers are a high-risk profession. They are always required to work closely with the open traffic lanes. Any distracted, speeding or intoxicated drivers might hit them, leading to their injuries and fatalities. From 1980 to 1992, a total of 54 fatalities involving flaggers in the construction industry have been reported. To protect flaggers and reduce their exposure to potential vehicular traffic, previous studies proposed and implemented the Automated Flagger Assistance Devices (AFADs). However, the AFADs have not been widely used in practice due to their costs. In addition to hiring a flagger to remotely operate an AFAD, the cost of an AFAD system alone ranges from $25,000 to $30,000 without the consideration of device maintenance. Instead of creating an assistance device, this paper proposed an automated flagging system (AFS) that can guide the traffic without the need for a flagger available on the site. The proposed system is composed of two modules: information capturing and decision-making. The information module is to monitor traffic conditions and retrieves useful information for the decision-making module to decide which sign (STOP or SLOW) to display in the LED panel. So far, a prototype was developed and tested in a laboratory environment. A vehicle detector was trained and integrated into the prototype. The laboratory test results indicated that the prototype could correctly show the STOP or SLOW sign based on the detection of simulated traffics.","PeriodicalId":179995,"journal":{"name":"Proceedings of the 1st Future of Construction Workshop at the International Conference on Robotics and Automation (ICRA 2022)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134077133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
—The integration of robots into the construction in- dustry shows promise in addressing challenges such as stagnant productivity and low efficiency. Recently, an increasing amount of research develops construction robots based on reinforcement learning (RL). However, most existing RL-based construction robots are trained to conduct specific tasks individually without cooperation. This paper proposes an approach that utilizes two RL-based construction robots (an unmanned ground vehicle and a robot arm) to collaboratively finish the task of window panel transport and installation in sequence without human intervention. Our experiment results show that the two con- struction robots can successfully collaborate to finish all tasks in an end-to-end manner after they are trained separately with a success rate of 79.6%.
{"title":"Deep Reinforcement Learning-based Construction Robots Collaboration for Sequential Tasks","authors":"Lei Huang, Zhengbo Zou","doi":"10.22260/icra2022/0015","DOIUrl":"https://doi.org/10.22260/icra2022/0015","url":null,"abstract":"—The integration of robots into the construction in- dustry shows promise in addressing challenges such as stagnant productivity and low efficiency. Recently, an increasing amount of research develops construction robots based on reinforcement learning (RL). However, most existing RL-based construction robots are trained to conduct specific tasks individually without cooperation. This paper proposes an approach that utilizes two RL-based construction robots (an unmanned ground vehicle and a robot arm) to collaboratively finish the task of window panel transport and installation in sequence without human intervention. Our experiment results show that the two con- struction robots can successfully collaborate to finish all tasks in an end-to-end manner after they are trained separately with a success rate of 79.6%.","PeriodicalId":179995,"journal":{"name":"Proceedings of the 1st Future of Construction Workshop at the International Conference on Robotics and Automation (ICRA 2022)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126075338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
—As the digital representation of the built environ- ment, BIM has been used to assist robot localization. Real-world images captured by the robot camera can be compared with BIM-rendered images to estimate the pose. However, there is a perception gap between the BIM environment and reality; image styles are typically too different to be matched. Hence, this study investigates an advanced image feature detection technique, D2-Net, to identify key points and descriptors on BIM-rendered and real-world images. These key features are further matched via K Nearest Neighbor Search and RANSAC. The ability to bridge the perception gap can be evaluated by the image matching performance, which is the Euclidean distance between the projected key points and the number of inliers. SIFT, as the traditional feature detection technique, was compared in this study. Results show that the average projection error of D2-Net is only 16.55 pixels, while the error of SIFT is 187.46 pixels. It demonstrates that the advanced D2-Net can be utilized to detect representative features on BIM-rendered and real-world images. The matched image pairs can be further utilized to estimate the robot pose in BIM. Overall, it aims to enhance the BIM-assisted localization and improve the robot’s reliability as a decision-making tool on-site.
{"title":"Accurate matching between BIM-rendered and real-world images","authors":"Houhao Liang, Justin K.W.Yeoh","doi":"10.22260/icra2022/0009","DOIUrl":"https://doi.org/10.22260/icra2022/0009","url":null,"abstract":"—As the digital representation of the built environ- ment, BIM has been used to assist robot localization. Real-world images captured by the robot camera can be compared with BIM-rendered images to estimate the pose. However, there is a perception gap between the BIM environment and reality; image styles are typically too different to be matched. Hence, this study investigates an advanced image feature detection technique, D2-Net, to identify key points and descriptors on BIM-rendered and real-world images. These key features are further matched via K Nearest Neighbor Search and RANSAC. The ability to bridge the perception gap can be evaluated by the image matching performance, which is the Euclidean distance between the projected key points and the number of inliers. SIFT, as the traditional feature detection technique, was compared in this study. Results show that the average projection error of D2-Net is only 16.55 pixels, while the error of SIFT is 187.46 pixels. It demonstrates that the advanced D2-Net can be utilized to detect representative features on BIM-rendered and real-world images. The matched image pairs can be further utilized to estimate the robot pose in BIM. Overall, it aims to enhance the BIM-assisted localization and improve the robot’s reliability as a decision-making tool on-site.","PeriodicalId":179995,"journal":{"name":"Proceedings of the 1st Future of Construction Workshop at the International Conference on Robotics and Automation (ICRA 2022)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116736826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
—As an integrated process in construction projects, quality assessment and management (QA&M) can be important to prevent failures during construction. The existing QA&M practice such as the evaluation of the geometric tolerance and surface qualities is mostly performed manually which can be labor-intensive and tedious. This study proposes a computational framework for a robot to perform automatic QA&M in unknown environments. The framework is composed of three parts: (1) motion planning; (2) defect detection; and (3) defect registration. The motion planning component generates efficient robotic path for autonomous exploration and surface inspection. The defect detection component quantifies surface anomalies within a user-defined area of interests through multiple sensor measurements. The defect registration component localizes the detected defects and registers the defects to a site model. To demonstrate the feasibility of the proposed framework, we present a user case for assessing geometric tolerance and surface quality of a 1500 mm (L) x 745 mm (W) x 1980 mm interior wall mockup. The result of the case study shows that the proposed framework has the potential to provide reliable geometric measurement and defect detection for gypsum wall panels in a lab environment.
{"title":"A Computational Framework For Robotic Quality Assessment and Management In Construction","authors":"Jingyang Liu, Yumeng Zhuang, Joshua Bard","doi":"10.22260/icra2022/0011","DOIUrl":"https://doi.org/10.22260/icra2022/0011","url":null,"abstract":"—As an integrated process in construction projects, quality assessment and management (QA&M) can be important to prevent failures during construction. The existing QA&M practice such as the evaluation of the geometric tolerance and surface qualities is mostly performed manually which can be labor-intensive and tedious. This study proposes a computational framework for a robot to perform automatic QA&M in unknown environments. The framework is composed of three parts: (1) motion planning; (2) defect detection; and (3) defect registration. The motion planning component generates efficient robotic path for autonomous exploration and surface inspection. The defect detection component quantifies surface anomalies within a user-defined area of interests through multiple sensor measurements. The defect registration component localizes the detected defects and registers the defects to a site model. To demonstrate the feasibility of the proposed framework, we present a user case for assessing geometric tolerance and surface quality of a 1500 mm (L) x 745 mm (W) x 1980 mm interior wall mockup. The result of the case study shows that the proposed framework has the potential to provide reliable geometric measurement and defect detection for gypsum wall panels in a lab environment.","PeriodicalId":179995,"journal":{"name":"Proceedings of the 1st Future of Construction Workshop at the International Conference on Robotics and Automation (ICRA 2022)","volume":"601 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123042352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
— When operating a construction robot, i.e., an excavator, the excavator operator’s unsafe behavior directly affects the underground utility damage occurrence during excavation process. Operator’s behavior is greatly affected by the environment and further the communication with other coworkers, i.e., spotter. In this paper, we propose a multi-user immersive operation and communication system for excavation. Further, we investigate how the different types of environments and operator-spotter communication channels affect operator’s attention demand and performance during excavation.
{"title":"Towards a Collaborative Future in Construction Robotics: A Human-centered Study in a Multi-user Immersive Operation and Communication System for Excavation","authors":"Di Liu, Youngjib Ham, Jeonghee Kim, Hangue Park","doi":"10.22260/icra2022/0016","DOIUrl":"https://doi.org/10.22260/icra2022/0016","url":null,"abstract":"— When operating a construction robot, i.e., an excavator, the excavator operator’s unsafe behavior directly affects the underground utility damage occurrence during excavation process. Operator’s behavior is greatly affected by the environment and further the communication with other coworkers, i.e., spotter. In this paper, we propose a multi-user immersive operation and communication system for excavation. Further, we investigate how the different types of environments and operator-spotter communication channels affect operator’s attention demand and performance during excavation.","PeriodicalId":179995,"journal":{"name":"Proceedings of the 1st Future of Construction Workshop at the International Conference on Robotics and Automation (ICRA 2022)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133952016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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