Abstract
The ability to resist to faults is a desired property in robotic systems. However, it is also hard to obtain, having to modify the behavior to face breakdowns. In this work we investigate the robustness against sensor faults in robots controlled by Boolean networks. These robots are subject to online adaptation—i.e., they adapt some structural properties while they actually act—for improving their performance at a simple task, namely phototaxis. We study their performance variation according to the number of faulty light sensors. The outcome is that Boolean network robots exhibit graceful degradation, as the performance decreases gently with the number of faulty sensors. We also observed that a moderate number of faulty sensors—especially if located contiguously—not only produces a negligible performance decrease, but it can be sometimes even beneficial. We argue that online adaptation is a key concept to achieve fault tolerance, allowing the robot to exploit the redundancy of sensor signals and properly tune the dynamics of the same Boolean network depending on the specific working sensor configuration.
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Notes
- 1.
This mostly thanks to their simple encoding and mutation.
- 2.
The number of changes is randomly chosen in 1–6.
- 3.
We consider a run successful if the robot reaches a point in the arena at a distance less than or equal to a given threshold value \(d_\theta \).
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Acknowledgements
AR acknowledges support from the PRIN 2022 research project of the Italian Ministry of University and Research titled Org(SB-EAI) – An Organizational Approach to the Synthetic Modeling of Cognition based on Synthetic Biology and Embodied AI (Grant Number: 20222HHXAX).
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Braccini, M., Baldini, P., Roli, A. (2024). An Investigation of Graceful Degradation in Boolean Network Robots Subject to Online Adaptation. In: Villani, M., Cagnoni, S., Serra, R. (eds) Artificial Life and Evolutionary Computation. WIVACE 2023. Communications in Computer and Information Science, vol 1977. Springer, Cham. https://doi.org/10.1007/978-3-031-57430-6_16
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