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

  2. For implementation please refer to GitHub:


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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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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).

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