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Toolkit for Dynamic Control Rapid Prototype Simulation System of Robots Applied in Space Experimental Cabin

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Intelligent Robotics and Applications (ICIRA 2021)

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Abstract

As the space environment is difficult to be recreated on the earth, it is essential to develop a software toolkit to validate the parameters designing for space robots. In this paper, a toolkit addressed for dynamic control rapid prototype simulation system of the space robot was presented. Based on the real-time control technology, the toolkit was consisted of real-time dynamic computing, redundant dual-arm control system, visual imaging and measurement and teleoperation. Specifically, the collision problem involved in the manipulator end effector and the target could be analyzed by contact dynamics models in the real-time dynamic computing module. Furthermore, a peg-in-hole (multi cores) assembly experiment involving the disassembly for the space electrical connectors was carried out, which was adopted to evaluate the simulation effect of toolkit. Our results showed that the connection between the space plug and socket with multi cores was well built up in the simulation environment. Moreover, the toolkit can be used to make simulations of on orbit operational missions by multiple of human-computer interaction, which is the key for the evaluation of control algorithm applied on the space robot.

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References

  1. Jin, R., Rocco, P., Geng, Y.: Observer-based fixed-time tracking control for space robots in task space. Acta Astronaut. 184, 35–45 (2021)

    Article  Google Scholar 

  2. Huang, P., Zhang, F., Cai, J., et al.: Dexterous tethered space robot: design, measurement, control, and experiment. IEEE Trans. Aerosp. Electron. Syst. 53(3), 1452–1468 (2017)

    Article  Google Scholar 

  3. Bessler, J., Schaake, L., Bidard, C., et al.: COVR–towards simplified evaluation and validation of collaborative robotics applications across a wide range of domains based on robot safety skills. Biosyst. Biorobot. 22, 123–126 (2019)

    Article  Google Scholar 

  4. Koenig, N., Howard, A.: Design and use paradigms for gazebo, an open-source multirobot simulator. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 3, pp. 2149–2154 (2004)

    Google Scholar 

  5. Zhu, K., Zhao, S.: AutoGami: A low-cost rapid prototyping toolkit for automated movable paper craft. In: 31st Annual CHI Conference on Human Factors in Computing Systems, pp. 661–670. Changing Perspectives, Paris (2013)

    Google Scholar 

  6. Irgenfried, S., Bergmann, S., Mohammadikaji, M., et al.: Image formation simulation for computer-aided inspection planning of machine vision systems. In: Proceedings of SPIE-The International Society for Optical Engineering. Automated Visual Inspection and machine Vision II, 1033406. Munich, Germany (2017)

    Google Scholar 

  7. Coevoet, E., Morales-Bieze, T., Largilliere, F., et al.: Software toolkit for modeling, simulation, and control of soft robots. Adv. Robot. 31(22), 1208–1224 (2017)

    Article  Google Scholar 

  8. Weirens, V.A., Hisamoto, C.S., Sheikh, S.I.: Simulation toolset for localization and control of swarming vehicles using random finite set theory. In: 2018 IEEE/ION Position, Location and Navigation Symposium, pp. 1286–1293. PLANS, Monterey (2018)

    Google Scholar 

  9. Haladjian, J.: The wearables development toolkit: an integrated development environment for activity recognition applications. Proc. ACM Interact. Mobile Wear. Ubiquit. Technol. 3(4), 134:1–134:26 (2019)

    Google Scholar 

  10. Haladjian, J., Hodaie, Z., et al.: KneeHapp: a bandage for rehabilitation of knee injuries. In: Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers, pp. 181–184. ACM, Osaka, Japan (2015)

    Google Scholar 

  11. Zhou, B., Koerger, H., et al.: Smart soccer shoe: monitoring foot-ball interaction with shoe integrated textile pressure sensor matrix. In: Proceedings of the 2016 ACM International Symposium on Wearable Computers, pp. 64–71. ACM, Heidelberg, Germany (2016)

    Google Scholar 

  12. Khan, A., Nicholson, J., Plötz, T.: Activity recognition for quality assessment of batting shots in cricket using a hierarchical representation. Proc. ACM Interact. Mobile Wear. Ubiquit. Technol. 1(3), 1–31 (2017)

    Article  Google Scholar 

  13. Marchesini, E., Farinelli, A.: Discrete deep reinforcement learning for mapless navigation. In: 2020 IEEE International Conference on Robotics and Automation, pp. 10688–10694. ICRA 2020, Paris, France (2020)

    Google Scholar 

  14. Rogachev, A.F., Melikhova, E.V.: Automation of the process of selecting hyperparameters for artificial neural networks for processing retrospective text information. In: 2nd International Conference on Mathematical Modeling of Technical and Economic Systems in Agriculture, MMTES 2020, 012012. Russian Federation (2020)

    Google Scholar 

  15. Rusanu, O.A., Cristea, L., et al.: Virtual robot arm controlled by hand gestures via Leap Motion Sensor. In: 10th Product Design, Robotics, Advanced Mechanical and Mechatronic Systems and Innovation Conference, PRASIC 2018, 012021. Brasov, Romania (2018)

    Google Scholar 

  16. Qualls, J., Canfield, S., Shibakov, A.: Kinematic control of a mobile robot performing manufacturing tasks on non-planar surfaces. J. Autom. Mob. Rob. Intell. Syst. 10(3), 12–21 (2016)

    Google Scholar 

  17. He, J., Sun, J.C., et al.: In-orbit background simulation study of SVOM/GRM. Astrophys. Space Sci. 365(10), 1–8 (2020)

    Article  Google Scholar 

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Acknowledgement

This research was supported by the National Key Research and Development Program of China under Grant No. 2018YFF0216004 and the National Natural Science Foundation of China with Grant No.11772188.

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Li, N., Ma, X., Zhang, C., Zou, H., Li, F. (2021). Toolkit for Dynamic Control Rapid Prototype Simulation System of Robots Applied in Space Experimental Cabin. In: Liu, XJ., Nie, Z., Yu, J., Xie, F., Song, R. (eds) Intelligent Robotics and Applications. ICIRA 2021. Lecture Notes in Computer Science(), vol 13016. Springer, Cham. https://doi.org/10.1007/978-3-030-89092-6_38

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  • DOI: https://doi.org/10.1007/978-3-030-89092-6_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-89091-9

  • Online ISBN: 978-3-030-89092-6

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