Construction Robot Teleoperation Safeguard Based on Real-Time Human Hand Motion Prediction
Publication: Journal of Construction Engineering and Management
Volume 148, Issue 7
Abstract
Robotic teleoperation has shown great potentials in various construction applications. With the advancements of virtual telepresence and motion capture technologies, bilateral teleoperation has been tested in precision construction operations, where a human operator can drive the motion of a remote robot with their natural body motions. A significant challenge is that because of the mismatch between robot mechanic design and the human body, such as a different number of joints of a robotic arm and a human arm, the recovered robot motions driven by human hand motions may not be desired, leading to unintended consequences including collision. This study presents a proactive collision avoidance system based on the real-time prediction of human hand motions. The proposed method, Feature-based Human-Motion Prediction (FHMP), stores streaming motion data into a data pool, quantifies the spatiotemporal relationship between gaze focus and hand movement trajectories, and segments and clusters the streaming data into different pattern groups based the motion pattern similarity. Different machine learning (ML) models are trained for each of the pattern groups. During the real-time prediction, whenever a pattern change is detected, the ML model is transitioned to a new model that matches the new pattern. A data buffering approach is used to reuse the old data and old ML model for a certain period of time before the new ML model is well trained, to ensure an uninterrupted real-time prediction of human hand motions. The gaze and hand motion data of a human subject experiment () for pipe skid maintenance was used to test the system in a virtual reality (VR) environment. The result shows that FHMP can support anticipatory collision avoidance in bilateral teleoperation with a better prediction performance. Future research could enable testing the method on real robots for more believable results.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
All data used in this paper can be found at: https://drive.google.com/drive/folders/1jKp3hxmziEo4WDZ2lt5jgNsM5JseA1Vf?usp=sharing.
Acknowledgments
This material is supported by the National Science Foundation (NSF) under Grants 1937053 and 2024784. Any opinions, findings, conclusions, or recommendations expressed in this paper are those of the authors and do not reflect the views of the NSF.
References
Adamides, G., G. Christou, C. Katsanos, M. Xenos, and T. Hadzilacos. 2014. “Usability guidelines for the design of robot teleoperation: A taxonomy.” IEEE Trans. Hum.-Mach. Syst. 45 (2): 256–262. https://doi.org/10.1109/THMS.2014.2371048.
AlfaLaval. 2020. “Instruction manual—Plate heat exchangers.” Accessed July 20, 2020. https://www.alfalaval.com/globalassets/documents/products/heat-transfer/plate-heat-exchangers/gasketed-plate-and-frame-heat-exchangers/industrial/instruction-manual-gphe-small-en.pdf.
Ardakani, M. M. G., J. H. Cho, R. Johansson, and A. Robertsson. 2014. “Trajectory generation for assembly tasks via bilateral teleoperation.” IFAC Proc. 47 (3): 10230–10235. https://doi.org/10.3182/20140824-6-ZA-1003.02559.
Aristidou, A., J. Lasenby, Y. Chrysanthou, and A. Shamir. 2018. “Inverse kinematics techniques in computer graphics: A survey.” In Proc., Computer Graphics Forum, 35–58. New York: Wiley.
Arthur, D., and S. Vassilvitskii. 2006. “-means++: The advantages of careful seeding.” In Proc., 18th Annual ACM-SIAM Symp. on Discrete Algorithms, 1027–1035. Philadelphia: Society for Industrial and Applied Mathematics.
Bai, H., S. Cai, N. Ye, D. Hsu, and W. S. Lee. 2015. “Intention-aware online POMDP planning for autonomous driving in a crowd.” In Proc., 2015 IEEE Int. Conf. on Robotics and Automation, 454–460. New York: IEEE.
Bajcsy, A., S. L. Herbert, D. Fridovich-Keil, J. F. Fisac, S. Deglurkar, A. D. Dragan, and C. J. Tomlin. 2019. “A scalable framework for real-time multi-robot, multi-human collision avoidance.” In Proc., 2019 Int. Conf. on Robotics and Automation, 936–943. New York: IEEE.
Berndt, D. J., and J. Clifford. 1994. “Using dynamic time warping to find patterns in time series.” In Proc., KDD workshop, 359–370. Palo Alto, CA: Association for the Advancement of Artificial Intelligence.
Borbély, B. J., and P. Szolgay. 2017. “Real-time inverse kinematics for the upper limb: A model-based algorithm using segment orientations.” Biomed. Eng. Online 16 (1): 21. https://doi.org/10.1186/s12938-016-0291-x.
Botchkarev, A. 2018. “Performance metrics (error measures) in machine learning regression, forecasting and prognostics: Properties and typology.” Preprint, submitted September 9, 2018. https://arxiv.org/abs/1809.03006.
Boucher, J.-D., U. Pattacini, A. Lelong, G. Bailly, F. Elisei, S. Fagel, P. F. Dominey, and J. Ventre-Dominey. 2012. “I reach faster when I see you look: Gaze effects in human–human and human–robot face-to-face cooperation.” Front. Neurorob. 6 (3): 3. https://doi.org/10.3389/fnbot.2012.00003.
Brennan, S. E., X. Chen, C. A. Dickinson, M. B. Neider, and G. J. Zelinsky. 2008. “Coordinating cognition: The costs and benefits of shared gaze during collaborative search.” Cognition 106 (3): 1465–1477. https://doi.org/10.1016/j.cognition.2007.05.012.
Bruce, A., and G. Gordon. 2004. “Better motion prediction for people-tracking.” In Proc., Int. Conf. on Robotics & Automation. New York: IEEE.
Butepage, J., M. J. Black, D. Kragic, and H. Kjellstrom. 2017. “Deep representation learning for human motion prediction and classification.” In Proc., IEEE Conf. on Computer Vision and Pattern Recognition, 6158–6166. New York: IEEE.
Corrales, J., F. Candelas, and F. Torres. 2011. “Safe human–robot interaction based on dynamic sphere-swept line bounding volumes.” Rob. Comput. Integr. Manuf. 27 (1): 177–185. https://doi.org/10.1016/j.rcim.2010.07.005.
Dietterich, T. G. 2002. “Machine learning for sequential data: A review.” In Proc., Joint IAPR Int. Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR), 15–30. Berlin: Springer.
Driggs-Campbell, K., R. Dong, and R. Bajcsy. 2018. “Robust, informative human-in-the-loop predictions via empirical reachable sets.” IEEE Trans. Intell. Veh. 3 (3): 300–309. https://doi.org/10.1109/TIV.2018.2843125.
Du, J., Y. Shi, C. Mei, J. Quarles, and W. Yan. 2016. “Communication by interaction: A multiplayer VR environment for building walkthroughs.” In Proc., Construction Research Congress 2016, 2281–2290. Reston, VA: ASCE.
Du, J., Y. Shi, Z. Zou, and D. Zhao. 2018a. “CoVR: Cloud-based multiuser virtual reality headset system for project communication of remote users.” J. Constr. Eng. Manage. 144 (2): 04017109. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001426.
Du, J., Z. Zou, Y. Shi, and D. Zhao. 2017. “Simultaneous data exchange between BIM and VR for collaborative decision making.” Comput. Civ. Eng. 2017 (1): 1–8. https://doi.org/10.1061/9780784480830.001.
Du, J., Z. Zou, Y. Shi, and D. Zhao. 2018b. “Zero latency: Real-time synchronization of BIM data in virtual reality for collaborative decision-making.” Autom. Constr. 85 (3): 51–64. https://doi.org/10.1016/j.autcon.2017.10.009.
Ellis, C. A., and S. A. Parbery. 2005. “Is smarter better? A comparison of adaptive, and simple moving average trading strategies.” Res. Int. Bus. Finance 19 (3): 399–411. https://doi.org/10.1016/j.ribaf.2004.12.009.
Emken, J. L., R. Benitez, and D. J. Reinkensmeyer. 2007. “Human-robot cooperative movement training: Learning a novel sensory motor transformation during walking with robotic assistance-as-needed.” J. Neuroeng. Rehabil. 4 (1): 8. https://doi.org/10.1186/1743-0003-4-8.
Everitt, B., S. Landau, M. Leese, and D. Stahl. 2011. Cluster analysis. Hoboken, NJ: Wiley.
Flacco, F., T. Kröger, A. De Luca, and O. Khatib. 2012. “A depth space approach to human-robot collision avoidance.” In Proc., 2012 IEEE Int. Conf. on Robotics and Automation, 338–345. New York: IEEE.
Fox, D., W. Burgard, and S. Thrun. 1997. “The dynamic window approach to collision avoidance.” IEEE Rob. Autom. Mag. 4 (1): 23–33. https://doi.org/10.1109/100.580977.
Fridovich-Keil, D., A. Bajcsy, J. F. Fisac, S. L. Herbert, S. Wang, A. D. Dragan, and C. J. Tomlin. 2020. “Confidence-aware motion prediction for real-time collision avoidance1.” Int. J. Rob. Res. 39 (2–3): 250–265. https://doi.org/10.1177/0278364919859436.
Friedman, J. H. 2001. “Greedy function approximation: A gradient boosting machine.” Ann. Stat. 2001 (Jan): 1189–1232. https://doi.org/10.1214/aos/1013203451.
Genolini, C., and B. Falissard. 2010. “KmL: K-means for longitudinal data.” Comput. Stat. 25 (2): 317–328. https://doi.org/10.1007/s00180-009-0178-4.
Ghosh, P., J. Song, E. Aksan, and O. Hilliges. 2017. “Learning human motion models for long-term predictions.” In Proc., 2017 Int. Conf. on 3D Vision (3DV), 458–466. New York: IEEE.
Giorgino, T. 2009. “Computing and visualizing dynamic time warping alignments in R: The dtw package.” J. Stat. Software 31 (7): 1–24. https://doi.org/10.18637/jss.v031.i07.
Görür, O. C., B. S. Rosman, G. Hoffman, and S. Albayrak. 2017. Toward integrating Theory of Mind into adaptive decision-making of social robots to understand human intention. Pretoria, South Africa: Council for Scientific and Industrial Research.
Grosz, B. J., and L. Hunsberger. 2006. “The dynamics of intention in collaborative activity.” Cognit. Syst. Res. 7 (2–3): 259–272. https://doi.org/10.1016/j.cogsys.2005.11.006.
Haddadin, S., A. Albu-Schaffer, A. De Luca, and G. Hirzinger. 2008. “Collision detection and reaction: A contribution to safe physical human-robot interaction.” In Proc., Int. Conf. on Intelligent Robots and Systems, 3356–3363. New York: IEEE.
Haddadin, S., A. De Luca, and A. Albu-Schäffer. 2017. “Robot collisions: A survey on detection, isolation, and identification.” IEEE Trans. Rob. 33 (6): 1292–1312. https://doi.org/10.1109/TRO.2017.2723903.
Hart, P. E., N. J. Nilsson, and B. Raphael. 1968. “A formal basis for the heuristic determination of minimum cost paths.” IEEE Trans. Syst. Sci. Cybern. 4 (2): 100–107. https://doi.org/10.1109/TSSC.1968.300136.
Hasegawa, Y., T. Kitamura, S. Sakaino, and T. Tsuji. 2020. “Bilateral control of elbow and shoulder joints using functional electrical stimulation between humans and robots.” IEEE Access 8 (Jan): 15792–15799. https://doi.org/10.1109/ACCESS.2020.2967466.
Hayhoe, M., and D. Ballard. 2005. “Eye movements in natural behavior.” Trends Cognit. Sci. 9 (4): 188–194. https://doi.org/10.1016/j.tics.2005.02.009.
Hiatt, L. M., A. M. Harrison, and J. G. Trafton. 2011. “Accommodating human variability in human-robot teams through theory of mind.” In Proc., 22nd Int. Joint Conf. on Artificial Intelligence. Palo Alto, CA: Association for the Advancement of Artificial Intelligence.
Huang, C.-M., and B. Mutlu. 2016. “Anticipatory robot control for efficient human-robot collaboration.” In Proc., 11th ACM/IEEE Int. Conf. on Human-Robot Interaction (HRI), 83–90. New York: IEEE.
Huang, D.-A., and K. M. Kitani. 2014. “Action-reaction: Forecasting the dynamics of human interaction.” In Proc., European Conf. on Computer Vision, 489–504. Berlin: Springer.
Huang, L., T. Kawamura, and H. Yamada. 2012. “Master-slave control method with force feedback for grasping soft objects using a teleoperation construction robot.” Int. J. Fluid Power 13 (2): 41–49. https://doi.org/10.1080/14399776.2012.10781052.
Huang, X., L. Zhang, B. Wang, F. Li, and Z. Zhang. 2018. “Feature clustering based support vector machine recursive feature elimination for gene selection.” Appl. Intell. 48 (3): 594–607. https://doi.org/10.1007/s10489-017-0992-2.
Huang, Z., and M. K. Ng. 1999. “A fuzzy k-modes algorithm for clustering categorical data.” IEEE Trans. Fuzzy Syst. 7 (4): 446–452. https://doi.org/10.1109/91.784206.
Itti, L., and C. Koch. 2001. “Computational modelling of visual attention.” Nat. Rev. Neurosci. 2 (3): 194–203. https://doi.org/10.1038/35058500.
Iwataki, S., H. Fujii, A. Moro, A. Yamashita, H. Asama, and H. Yoshinada. 2015. “Visualization of the surrounding environment and operational part in a 3DCG model for the teleoperation of construction machines.” In Proc., Int. Symp. on System Integration (SII), 81–87. New York: IEEE.
Johansson, R. S., G. Westling, A. Bäckström, and J. R. Flanagan. 2001. “Eye–hand coordination in object manipulation.” J. Neurosci. 21 (17): 6917–6932. https://doi.org/10.1523/JNEUROSCI.21-17-06917.2001.
Johnson, S. C. 1967. “Hierarchical clustering schemes.” Psychometrika 32 (3): 241–254. https://doi.org/10.1007/BF02289588.
Johnston, F., J. Boyland, M. Meadows, and E. Shale. 1999. “Some properties of a simple moving average when applied to forecasting a time series.” J. Oper. Res. Soc. 50 (12): 1267–1271. https://doi.org/10.1057/palgrave.jors.2600823.
Kanehiro, F., H. Hirukawa, K. Kaneko, S. Kajita, K. Fujiwara, K. Harada, and K. Yokoi. 2004. “Locomotion planning of humanoid robots to pass through narrow spaces.” In Proc., IEEE Int. Conf. on Robotics and Automation, 2004, 604–609. New York: IEEE.
Karaman, S., and E. Frazzoli. 2011. “Sampling-based algorithms for optimal motion planning.” Int. J. Rob. Res. 30 (7): 846–894. https://doi.org/10.1177/0278364911406761.
Ke, G., Q. Meng, T. Finley, T. Wang, W. Chen, W. Ma, Q. Ye, and T.-Y. Liu. 2017. “LightGBM: A highly efficient gradient boosting decision tree.” In Proc., Advances in Neural Information Processing Systems, 3146–3154. San Diego: Neural Information Processing Systems.
Keogh, E. J., and M. J. Pazzani. 2000. “Scaling up dynamic time warping for datamining applications.” In Proc., 6th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining, 285–289. New York: Association for Computing Machinery.
Kinnunen, T., I. Sidoroff, M. Tuononen, and P. Fränti. 2011. “Comparison of clustering methods: A case study of text-independent speaker modeling.” Pattern Recognit. Lett. 32 (13): 1604–1617. https://doi.org/10.1016/j.patrec.2011.06.023.
Kohler, M. 1997. Using the Kalman filter to track human interactive motion: Modelling and initialization of the Kalman filter for translational motion. University Park, PA: CiteSeerX.
Kousik, S., S. Vaskov, F. Bu, M. Johnson-Roberson, and R. Vasudevan. 2020. “Bridging the gap between safety and real-time performance in receding-horizon trajectory design for mobile robots.” Int. J. Rob. Res. 39 (12): 1419–1469. https://doi.org/10.1177/0278364920943266.
Kovar, L., M. Gleicher, and F. Pighin. 2008. “Motion graphs.” In ACM SIGGRAPH 2008 classes, 1–10. New York: Association for Computing Machinery.
Krüger, J., B. Nickolay, P. Heyer, and G. Seliger. 2005. “Image based 3D surveillance for flexible man-robot-cooperation.” CIRP Ann. 54 (1): 19–22. https://doi.org/10.1016/S0007-8506(07)60040-7.
Land, M. F., and M. Hayhoe. 2001. “In what ways do eye movements contribute to everyday activities?” Vis. Res. 41 (25–26): 3559–3565. https://doi.org/10.1016/S0042-6989(01)00102-X.
Lasota, P. A., and J. A. Shah. 2015. “Analyzing the effects of human-aware motion planning on close-proximity human–robot collaboration.” Hum. Factors 57 (1): 21–33. https://doi.org/10.1177/0018720814565188.
Latombe, J.-C. 2012. Robot motion planning. Berlin: Springer.
Leisch, F. 2006. “A toolbox for k-centroids cluster analysis.” Comput. Stat. Data Anal. 51 (2): 526–544. https://doi.org/10.1016/j.csda.2005.10.006.
Lin, J., E. Keogh, L. Wei, and S. Lonardi. 2007. “Experiencing SAX: A novel symbolic representation of time series.” Data Min. Knowl. Discovery 15 (2): 107–144. https://doi.org/10.1007/s10618-007-0064-z.
Lo, S.-Y., C.-A. Cheng, and H.-P. Huang. 2016. “Virtual impedance control for safe human-robot interaction.” J. Intell. Rob. Syst. 82 (1): 3–19. https://doi.org/10.1007/s10846-015-0250-y.
Magidson, J., and J. Vermunt. 2002. “Latent class models for clustering: A comparison with K-means.” Can. J. Marketing Res. 20 (1): 36–43.
Mainprice, J., and D. Berenson. 2013. “Human-robot collaborative manipulation planning using early prediction of human motion.” In Proc., Int. Conf. on Intelligent Robots and Systems, 299–306. New York: IEEE.
Martinez, J., M. J. Black, and J. Romero. 2017. “On human motion prediction using recurrent neural networks.” In Proc., IEEE Conf. on Computer Vision and Pattern Recognition, 2891–2900. New York: IEEE.
Matsumoto, K., S. Wakabayashi, F. Penin, M. Nohmi, H. Ueno, T. Yoshida, and Y. Fukase. 1999. “Teleoperation control of ETS-7 robot arm for on-orbit truss construction.” In Proc., Artificial Intelligence, Robotics and Automation in Space, 313. Paris: European Space Agency.
Meltzoff, A. N., and R. Brooks. 2001. “Like me as a building block for understanding other minds: Bodily acts, attention, and intention.” In Intentions and intentionality: Foundations of social cognition. Cambridge, MA: MIT Press.
Mohammed, A., B. Schmidt, and L. Wang. 2017. “Active collision avoidance for human–robot collaboration driven by vision sensors.” Int. J. Comput. Integr. Manuf. 30 (9): 970–980. https://doi.org/10.1080/0951192X.2016.1268269.
Nail, P. R., and K. A. Boniecki. 2011. Inconsistency in cognition: Cognitive dissonance. Washington, DC: American Psychological Association.
Naranjo, J. E., E. C. Lozada, H. I. Espín, C. Beltran, C. A. García, and M. V. García. 2018. “Flexible architecture for transparency of a bilateral tele-operation system implemented in mobile anthropomorphic robots for the oil and gas industry.” IFAC-PapersOnLine 51 (8): 239–244. https://doi.org/10.1016/j.ifacol.2018.06.383.
Paden, B., M. Čáp, S. Z. Yong, D. Yershov, and E. Frazzoli. 2016. “A survey of motion planning and control techniques for self-driving urban vehicles.” IEEE Trans. Intell. Veh. 1 (1): 33–55. https://doi.org/10.1109/TIV.2016.2578706.
Park, C., J. Pan, and D. Manocha. 2013. “Real-time optimization-based planning in dynamic environments using GPUs.” In Proc., 2013 IEEE Int. Conf. on Robotics and Automation, 4090–4097. New York: IEEE.
Pavlovic, V., J. M. Rehg, and J. MacCormick. 2000. Learning switching linear models of human motion. San Diego: Neural Information Processing Systems.
Peng, Z., T. Genewein, and D. A. Braun. 2014. “Assessing randomness and complexity in human motion trajectories through analysis of symbolic sequences.” Front. Hum. Neurosci. 8 (3): 168. https://doi.org/10.3389/fnhum.2014.00168.
Powell, M. J. 1994. “A direct search optimization method that models the objective and constraint functions by linear interpolation.” In Advances in optimization and numerical analysis, 51–67. Berlin: Springer.
Robla-Gómez, S., V. M. Becerra, J. R. Llata, E. Gonzalez-Sarabia, C. Torre-Ferrero, and J. Perez-Oria. 2017. “Working together: A review on safe human-robot collaboration in industrial environments.” IEEE Access 5: 26754–26773. https://doi.org/10.1109/ACCESS.2017.2773127.
Robotics, R. 2016. “Baxter datasheet.” Accessed February 6, 2020. https://sdk.rethinkrobotics.com/wiki/Home.
Rudenko, A., L. Palmieri, M. Herman, K. M. Kitani, D. M. Gavrila, and K. O. Arras. 2019. “Human motion trajectory prediction: A survey.” Int. J. Rob. Res. 39 (8): 895–935. https://doi.org/10.1177/0278364920917446.
Saaid, F., D. Nur, and R. King. 2012. Change points detection of vector autoregressive model using SDVAR algorithm. Wollongong, Australia: Univ. of Wollongong.
Savaresi, S. M., and D. L. Boley. 2001. “On the performance of bisecting K-means and PDDP.” In Proc., 2001 SIAM Int. Conf. on Data Mining, 1–14. Washington, DC: SIAM.
Savitzky, A., and M. J. Golay. 1964. “Smoothing and differentiation of data by simplified least squares procedures.” Anal. Chem. 36 (8): 1627–1639. https://doi.org/10.1021/ac60214a047.
Schlimmer, J. C., and D. Fisher. 1986. “A case study of incremental concept induction.” In Proc., AAAI, 496–501. Palo Alto, CA: Association for the Advancement of Artificial Intelligence.
Schmidt, B., and L. Wang. 2014. “Depth camera based collision avoidance via active robot control.” J. Manuf. Syst. 33 (4): 711–718. https://doi.org/10.1016/j.jmsy.2014.04.004.
Shi, Y., J. Du, E. Ragan, K. Choi, and S. Ma. 2018. “Social influence on construction safety behaviors: A multi-user virtual reality experiment.” In Proc., Construction Research Congress, 147–183.
Sisbot, E. A., and R. Alami. 2012. “A human-aware manipulation planner.” IEEE Trans. Rob. 28 (5): 1045–1057. https://doi.org/10.1109/TRO.2012.2196303.
Squyres, S. W., R. E. Arvidson, E. T. Baumgartner, J. F. Bell, P. R. Christensen, S. Gorevan, K. E. Herkenhoff, G. Klingelhöfer, M. B. Madsen, and R. V. Morris. 2003. “Athena Mars rover science investigation.” J. Geophys. Res. Planets 108 (12): 1029. https://doi.org/10.1029/2003JE002121.
Suita, K., Y. Yamada, N. Tsuchida, K. Imai, H. Ikeda, and N. Sugimoto. 1995. “A failure-to-safety ‘Kyozon’ system with simple contact detection and stop capabilities for safe human-autonomous robot coexistence.” In Proc., 1995 IEEE Int. Conf. on Robotics and Automation, 3089–3096. New York: IEEE.
Takakura, S., T. Murakami, and K. Ohnishi. 1989. “An approach to collision detection and recovery motion in industrial robot.” In Proc., 15th Annual Conference of IEEE Industrial Electronics Society, 421–426. New York: IEEE.
Tang, X., and H. Yamada. 2011. “Tele-operation construction robot control system with virtual reality technology.” Procedia Eng. 15 (3): 1071–1076. https://doi.org/10.1016/j.proeng.2011.08.198.
Tobii. 2020a. “How do Tobii Eye Trackers work?” Accessed July 19, 2020. https://www.tobiipro.com/learn-and-support/learn/eye-tracking-essentials/how-do-tobii-eye-trackers-work/.
Tobii. 2020b. “Tobii Pro VR Integration based on HTC Vive HMD.” Accessed July 19, 2020. https://www.tobiipro.com/product-listing/vr-integration/.
Tomasello, M. 1995. “Joint attention as social cognition.” In Joint attention: Its origins and role in development. East Sussex, UK: Psychology Press.
Truong, C., L. Oudre, and N. Vayatis. 2020. “Selective review of offline change point detection methods.” Signal Process. 167 (34): 107299. https://doi.org/10.1016/j.sigpro.2019.107299.
Truong, D. Q., B. N. M. Truong, N. T. Trung, S. A. Nahian, and K. K. Ahn. 2017. “Force reflecting joystick control for applications to bilateral teleoperation in construction machinery.” Int. J. Precis. Eng. Manuf. 18 (3): 301–315. https://doi.org/10.1007/s12541-017-0038-z.
Vertegaal, R., R. Slagter, G. Van der Veer, and A. Nijholt. 2001. “Eye gaze patterns in conversations: There is more to conversational agents than meets the eyes.” In Proc., SIGCHI Conf. on Human Factors in Computing Systems, 301–308. New York: Association for Computing Machinery.
Wagstaff, K., C. Cardie, S. Rogers, and S. Schroedl. 2001. “Constrained k-means clustering with background knowledge.” In Proc., ICML, 577–584. San Francisco: Morgan Kaufmann Publication.
Wambui, G. D., G. A. Waititu, and A. Wanjoya. 2015. “The power of the pruned exact linear time (PELT) test in multiple changepoint detection.” Am. J. Theor. Appl. Stat. 4 (6): 581–586. https://doi.org/10.11648/j.ajtas.20150406.30.
Wang, L., B. Schmidt, and A. Y. Nee. 2013. “Vision-guided active collision avoidance for human-robot collaborations.” Manuf. Letters 1 (1): 5–8. https://doi.org/10.1016/j.mfglet.2013.08.001.
Wikman, T. S., M. S. Branicky, and W. S. Newman. 1993. “Reflexive collision avoidance: A generalized approach.” In Proc., IEEE Int. Conf. on Robotics and Automation, 31–36. New York: IEEE.
Wyart, V., and E. Koechlin. 2016. “Choice variability and suboptimality in uncertain environments.” Curr. Opin. Behav. Sci. 11 (Sep): 109–115. https://doi.org/10.1016/j.cobeha.2016.07.003.
Yuan, C., and H. Yang. 2019. “Research on K-value selection method of K-means clustering algorithm.” J. Multidiscip. Sci. J. 2 (2): 226–235. https://doi.org/10.3390/j2020016.
Zhang, T., R. Ramakrishnan, and M. Livny. 1996. “BIRCH: An efficient data clustering method for very large databases.” ACM Sigmod Rec. 25 (2): 103–114. https://doi.org/10.1145/235968.233324.
Zhou, T., Q. Zhu, and J. Du. 2020. “Intuitive robot teleoperation for civil engineering operations with virtual reality and deep learning scene reconstruction.” Adv. Eng. Inf. 46 (2): 101170. https://doi.org/10.1016/j.aei.2020.101170.
Zhu, Q., J. Du, Y. Shi, and P. Wei. 2021. “Neurobehavioral assessment of force feedback simulation in industrial robotic teleoperation.” Autom. Constr. 126 (4): 103674. https://doi.org/10.1016/j.autcon.2021.103674.
Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 148 • Issue 7 • July 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: May 24, 2021
Accepted: Feb 8, 2022
Published online: Apr 19, 2022
Published in print: Jul 1, 2022
Discussion open until: Sep 19, 2022
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.
Cited by
- Fang Xu, Tianyu Zhou, Yang Ye, Jing Du, Augmented Telepresence: Enhancing Robot Arm Control with Mixed Reality for Dexterous Manipulation, Construction Research Congress 2024, 10.1061/9780784485262.074, (727-738), (2024).
- Fangxiao Li, Yuqing Hu, Robert M. Leicht, A Schema for Robotics Operations in Construction, Computing in Civil Engineering 2023, 10.1061/9780784485224.089, (739-746), (2024).
- Jiannan Cai, Ao Du, Xiaoyun Liang, Shuai Li, Prediction-Based Path Planning for Safe and Efficient Human–Robot Collaboration in Construction via Deep Reinforcement Learning, Journal of Computing in Civil Engineering, 10.1061/(ASCE)CP.1943-5487.0001056, 37, 1, (2023).
- Xiaolu Xia, Tianyu Zhou, Jing Du, Nan Li, Human motion prediction for intelligent construction: A review, Automation in Construction, 10.1016/j.autcon.2022.104497, 142, (104497), (2022).