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A mechanism for real-time decision making and system maintenance for resource constrained robotic systems through ReFrESH

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Abstract

Robot operating environments and the status of robots are complex and varying, so it is practically impossible for a robotics designer to anticipate all system configurations to successfully complete a task prior to deployment. Therefore, a mechanism for dynamic decision making and configuration synthesis that copes with system fault and uncertainty is necessary. This paper implements such a mechanism within a self-adaptive framework (ReFrESH). The goal of this presented mechanism is to provide diagnosability and maintainability to manage the system performance during task execution in the presence of unexpected uncertainties. Specifically, the functionality of the proposed mechanism include: (1) detection of system performance degradation; (2) diagnosis and locate of the fault module; (3) synthesis of feasible task configurations; (4) selection of the optimal one. We illustrate the feasibility of the proposed mechanism through a visual servoing task.

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Notes

  1. Bitstream is the compiled hardware accelerator module in FPGA.

  2. For implementation please refer to GitHub: https://github.com/cuiyanzhe/ReFrESH.

References

  • Cui, Y., Voyles, R., He, M., Jiang, G., MH., M. (2012). A self-adaptation framework for heterogeneous miniature search and rescue robots. In Safety Security and Rescue Robotics (SSRR), 2012 IEEE International Workshop on SSRR (pp. 1–7).

  • Cui, Y., Voyles, R. & Mahoor, M. (2013). Refresh: A self-adaptive architecture for autonomous embedded systems. In Automation Science and Engineering (CASE), 2013 IEEE International Conference on CASE (pp. 850–855). doi:10.1109/CoASE.2013.6654042.

  • Cui, Y., Voyles, R., Lane, J. & Mahoor, M. (2014a). Refresh: A self-adaptation framework to support fault tolerance in field mobile robots. In Intelligent Robots and Systems (IROS 2014), 2014 IEEE/RSJ International Conference on IROS 2014 (pp. 1576–1582). doi:10.1109/IROS.2014.6942765.

  • Cui, Y., Voyles, R., Nawrocki, R., & Jiang, G. (2014b). Morphing bus: A new paradigm in peripheral interconnect bus. IEEE Transactions on Components, Packaging and Manufacturing Technology, 4(2), 341–351. doi:10.1109/TCPMT.2013.2273663.

    Article  Google Scholar 

  • Dasgupta, B., & Mruthyunjaya, T. (2000). The stewart platform manipulator: A review. Mechanism and Machine Theory, 35(1), 15–40.

    Article  MATH  MathSciNet  Google Scholar 

  • Epifani, I., Ghezzi, C., Mirandola, R. & Tamburrelli, G. (2009) Model evolution by run-time parameter adaptation. In Proceedings of the 31st International Conference on Software Engineering, ICSE ’09 (pp. 111–121). Washington, DC: IEEE Computer Society. doi:10.1109/ICSE.2009.5070513.

  • Garlan, D., Cheng, S. W., Huang, A. C., Schmerl, B., & Steenkiste, P. (2004). Rainbow: Architecture-based self-adaptation with reusable infrastructure. Computer, 37(10), 46–54. doi:10.1109/MC.2004.175.

    Article  Google Scholar 

  • Georgas, J.C. & Taylor, R.N. (2008). Policy-based self-adaptive architectures: A feasibility study in the robotics domain. In Proceedings of the 2008 International Workshop on Software Engineering for Adaptive and Self-managing Systems, SEAMS ’08 (pp. 105–112). New York: ACM. doi:10.1145/1370018.1370038.

  • Gerkey, B., & Mataric, M. (2002). Sold!: auction methods for multirobot coordination. IEEE Transactions on Robotics and Automation, 18(5), 758–768. doi:10.1109/TRA.2002.803462.

    Article  Google Scholar 

  • Grindal, M., Lindstrm, B., Offutt, J., & Andler, S. (2006). An evaluation of combination strategies for test case selection. Empirical Software Engineering, 11(4), 583–611. doi:10.1007/s10664-006-9024-2.

    Article  Google Scholar 

  • He, M., Cui, Y., Mahoor, M. & Voyles, R. (2012). A heterogeneous modules interconnection architecture for FPGA-based partial dynamic reconfiguration. In Reconfigurable Communication-centric Systems-on-Chip (ReCoSoC), 2012 7th International Workshop on ReCoSoC (pp. 1 –7). doi:10.1109/ReCoSoC.2012.6322887.

  • Kramer, J. & Magee, J. (2007). Self-managed systems: An architectural challenge. In Future of Software Engineering, 2007, FOSE ’07 (pp. 259–268). doi:10.1109/FOSE.2007.19.

  • Last, P., Budde, C. & Hesselbach, J. (2005). Self-calibration of the hexa-parallel-structure. In Automation Science and Engineering, 2005, IEEE International Conference on Automation Science and Engineering, 2005 (pp. 393–398). doi:10.1109/COASE.2005.1506801.

  • Mangharam, R. & Pajic, M. (2009). Embedded virtual machines for robust wireless control systems. In Distributed Computing Systems Workshops, 2009, 29th IEEE International Conference on ICDCS Workshops ’09 (pp. 38–43). doi:10.1109/ICDCSW.2009.31.

  • McIntyre, M., Dixon, W., Dawson, D., & Walker, I. (2005). Fault identification for robot manipulators. IEEE Transactions on Robotics, 21(5), 1028–1034. doi:10.1109/TRO.2005.851356.

    Article  Google Scholar 

  • Michael, N., Shen, S., Mohta, K., Mulgaonkar, Y., Kumar, V., Nagatani, K., et al. (2012). Collaborative mapping of an earthquake-damaged building via ground and aerial robots. J Field Robot, 29(5), 832–841.

    Article  Google Scholar 

  • Nie, C., & Leung, H. (2011). A survey of combinatorial testing. ACM Computing Surveys, 43(2), 11:1–11:29. doi:10.1145/1883612.1883618.

    Article  Google Scholar 

  • Parker, L. (1998). Alliance: An architecture for fault tolerant multirobot cooperation. IEEE Transactions on Robotics and Automation, 14(2), 220–240. doi:10.1109/70.681242.

    Article  Google Scholar 

  • Pierrot, F., & Uchiyama, M. (1990). A new design of a 6-DOF parallel robot. Journal of Robotics and Mechatronics, 2(4), 308–315.

    Google Scholar 

  • Stewart, D., Volpe, R., & Khosla, P. (1997). Design of dynamically reconfigurable real-time software using port-based objects. IEEE Transactions on Software Engineering, 23(12), 759–776. doi:10.1109/32.637390.

    Article  Google Scholar 

  • Tung, Y.W. & Aldiwan, W. (2000). Automating test case generation for the new generation mission software system. In 2000 IEEE Aerospace Conference Proceedings (Vol. 1, pp. 431–437). doi:10.1109/AERO.2000.879426.

  • van Hoorn, A., Waller, J. & Hasselbring, W. (2012). Kieker: A framework for application performance monitoring and dynamic software analysis. In Proceedings of the Third Joint WOSP/SIPEW International Conference on Performance Engineering, ICPE ’12 (pp. 247–248). New York: ACM. doi:10.1145/2188286.2188326.

  • Vig, L., & Adams, J. (2006). Multi-robot coalition formation. IEEE Transactions on Robotics, 22(4), 637–649. doi:10.1109/TRO.2006.878948.

    Article  Google Scholar 

  • Voyles, R., Povilus, S., Mangharam, R. & Li, K. (2010). Reconode: A reconfigurable node for heterogeneous multi-robot search and rescue. In Safety Security and Rescue Robotics (SSRR), 2010 IEEE International Workshop on SSRR (pp. 1–7). doi:10.1109/SSRR.2010.5981569.

  • Zhang, Y. & Parker, L. (2012). Task allocation with executable coalitions in multirobot tasks. In Robotics and Automation (ICRA), 2012 IEEE International Conference on ICRA (pp. 3307–3314). doi:10.1109/ICRA.2012.6224910.

  • Zhang, Y., & Parker, L. (2013). IQ-ASyMTRe: Forming executable coalitions for tightly coupled multirobot tasks. IEEE Transactions on Robotics, 29(2), 400–416. doi:10.1109/TRO.2012.2228135.

    Article  Google Scholar 

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Acknowledgments

This work was supported by National Science Foundation Grants CNS-0923518, CNS-1450342 and IIS-1111568 with additional support from the NSF Center for Robots and Sensors for the Human Well-Being (RoSe-HUB).

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Authors and Affiliations

  1. College of Engineering, Purdue University, West Lafayette, USA

    Yanzhe Cui & Akshay Krishnamoorthy

  2. Purdue Polytechnic, Purdue University, West Lafayette, USA

    Richard M. Voyles & Josh T. Lane

  3. Department of Electrical and Computer Engineering, University of Denver, Denver, USA

    Mohammad H. Mahoor

Authors
  1. Yanzhe Cui
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  2. Richard M. Voyles
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  3. Josh T. Lane
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  4. Akshay Krishnamoorthy
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  5. Mohammad H. Mahoor
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Correspondence to Yanzhe Cui.

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Cui, Y., Voyles, R.M., Lane, J.T. et al. A mechanism for real-time decision making and system maintenance for resource constrained robotic systems through ReFrESH. Auton Robot 39, 487–502 (2015). https://doi.org/10.1007/s10514-015-9472-x

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