Abstract
We investigate the effect of errors in collective robotic construction (CRC) on both construction time and the probability of correctly completing a specified structure. We ground our investigation in the TERMES distributed construction system, which uses local sensing and stigmergic rules that enable robots to navigate and build 3D structures. We perform an in depth analysis and categorization of action failures in CRC systems. We present an approach to mitigating action failures and preventing errors that prohibit completion of a structure by adding predictive local checks. We show that the predictive local checks can increase the probability of success by orders of magnitude in large structures. This work demonstrates the need to consider both construction time and the effect of errors in collective robotic construction.
The first three authors contributed equally to this work.
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Acknowledgments
This project was funded by the Packard Fellowship for Science and Engineering, GETTYLABS, and the National Science Foundation (NSF) Grant #1846340 and #2042411.
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Chen, J., Liu, Y., Pacheck, A., Kress-Gazit, H., Napp, N., Petersen, K. (2022). Errors in Collective Robotic Construction. In: Matsuno, F., Azuma, Si., Yamamoto, M. (eds) Distributed Autonomous Robotic Systems. DARS 2021. Springer Proceedings in Advanced Robotics, vol 22. Springer, Cham. https://doi.org/10.1007/978-3-030-92790-5_21
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DOI: https://doi.org/10.1007/978-3-030-92790-5_21
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