Abstract
More effective operation of spacecraft control panels is possible by means of a robot manipulator. Either emulation or automatic robot operation may be employed. The conditions determining the selection of the control mode (emulation or automatic robot operation) are refined.
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REFERENCES
Kryuchkov, B.I., Dovzhenko, V.A., Onufrienko, Yu.I., and Gorlova, V.I., RF Inventor’s Certificate no. 2016621418, 2016.
Kryuchkov, B.I., Usov, V.M., Yaropolov, V.I., et al., Specific professional activities of cosmonauts in the lunar missions, Pilotiruemye Polety Kosm., 2016, no. 2 (19), pp. 35–58.
Karpov, A.A., Kryuchkov, B.I., Rogatkin, D.A., and Usov, V.M., Conceptual approaches to the use of service robots: common problems of implementation (by the examples of manned cosmonautics and high-tech medicine), Biotekhnosfera, 2013, no. 6, pp. 48–59.
Kondratenko, M.V., Titov, K.A., and Salaev, A.M., Space robotic systems on the International Space Station, Pilotiruemye Polety Kosm., 2014, no. 3 (12), pp. 80–91.
Tyapchenko, Yu.A., Integrated display system of information of the Soyuz-TMA spacecraft and the console of the manual control loop of the Russian segment of the Alpha ISS, Tr. Tsentr. Aerogidrodin. Inst., 1999, vol. 2, no. 2640, pp. 578–593.
Zinchenko, V.P., Munipov, V.M., and Smolyan, G.L., Ergonomicheskie osnovy organizatsii truda (Ergonomic Basics of Work Organization), Moscow: Ekonomika, 1974.
Minitaeva, A.M., Organization of a human-machine interface taking into account the intellectualization of the interaction of a man and a computer complex, Progr. Prod. Sist., 2013, no. 3, pp. 104–107.
Collaborative robot CR5 series, NPO Androidnaya Tekhnika. https://npo-at.com/production/kollaborativnyj-robot-serii-cr5#descriptiontab/. Accessed June 25, 2021.
Sokhin, I.G., Dovzhenko, V.A., Burdin, B.V., et al., Experimental ergonomic studies of remote control of an anthropomorphic robotic system by cosmonauts during service operations of spacecrafts and lunar infrastructure, Materialy XI Mezhdunarodnoi nauchno-prakticheskoi konferentsii “Pilotiruemye polety v kosmos” (Proc. XI Int. Sci.-Pract. Conf. “Manned Space Flights”), Zvezdnyi Gorodok: Nauchno-Issled. Ispyt. Tsentr Podgotovki Kosm. im. Yu.A. Gagarina, 2015, pp. 31–33.
Zenkevich, S.L. and Yushchenko, A.S., Osnovy upravleniya manipulyatsionnymi robotami: Uchebnik dlya vuzov (Fundamentals of Manipulation Robot Control: Manual for Higher Education Institutions), Moscow: Mosk. Gos. Tekh. Univ. im. N.E. Baumana, 2004.
He, K., Zhang, X., Ren, S., and Sun, J., Deep residual learning for image recognition, Proc. 2016 IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Red Hook, NY: Curran Assoc., 2016, pp. 770–778.
Rosten, E. and Drummond, T., Machine learning for high-speed corner detection, Proc. 9th European Conf. on Computer Vision, Graz, Austria, May 7–13, 2006, Berlin: Springer-Verlag, 2006, pp. 430–443.
Forssyth, D.A. and Ponce, J., Computer Vision: a Modern Approach, Boston: Pearson, 2003, pp. 519–539.
Kim, N. and Bodunkov, N., Automated decision making in road traffic monitoring by on-board unmanned aerial vehicle system, in Computer Vision in Control Systems-3: Aerial and Satellite Image Processing, Favor-skaya, M. and Lakhmi, C.J., Eds., Cham: Springer-Verlag, 2018, ch. 6.
Os’kin, D.A., Dyda, A.A., and Konstantinova, E.A., Neural network modeling of a kinematics problem for a manipulation robot, Sovrem. Naukoemkie Tekhnol., 2015, no. 12-2, pp. 254–257.
Titov, V.V. and Timofeev, A.V., Neural network methods of planning and control of the motion of complex mechatronic systems in extreme environments, Materialy konferentsii “Informatsionnye tekhnologii v upravlenii (ITU-2012)” (Proc. Conf. “Information Technologies in Management (ITM-2012)”), St. Petersburg: Tsentr. Nauchno-Issled. Inst. Elektropribor, 2012, pp. 816–828.
Rostov, N.V., Analysis of algorithms to solve the inverse problems of kinematics in robot motion control systems, Nauchno-Tekh. Ved. S-Peterb. Gos. Pedagog. Univ., Inf., Telekom., Upr., 2014, no. 5 (205), pp. 93–99.
Bol’shakov, A.A., Brovkova, M.B., Glazkov, V.P., et al., Sistemy iskusstvennogo intellekta v mekhatronike: uchebnoe posobie (Artificial Intelligence Systems in Mechatronics: Manual), Saratov: Saratov. Gos. Tekh. Univ. im. Yu.A. Gagarina, 2014.
Razin, V.V. and Tuzovskii, A.F., Decision-making method based on situation analysis and semantic technologies, Izv. Tomsk. Politekh. Univ., 2012, vol. 321, no. 5, pp. 188–193.
Solov’ev, V.D., Dobrov, B.V., Ivanov, V.V., and Lukashevich, N.V., Ontologii i tezaurusy: uchebnoe posobie (Ontologies and Thesauri: Manual), Moscow, 2006.
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Translated by B. Gilbert
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Kim, N.V., Chebotarev, Y.S. Automated Operation of a Spacecraft Control-Panel. Russ. Engin. Res. 42, 82–84 (2022). https://doi.org/10.3103/S1068798X22010099
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DOI: https://doi.org/10.3103/S1068798X22010099