Document Type
Article
Publication Date
3-28-2025
Abstract
Bio-inspired robot controllers are becoming more complex as we strive to make them more robust to, and flexible in, noisy, real-world environments. A stable heteroclinic network (SHN) is a dynamical system that produces cyclical state transitions using noisy input. SHN-based robot controllers enable sensory input to be integrated at the phase-space level of the controller, thus simplifying sensor-integrated, robot control methods. In this work, we investigate the mechanism that drives branching state trajectories in SHNs. We liken the branching state trajectories to decision-splits imposed into the system, which opens the door for more sophisticated controls-all driven by sensory input. This work provides guidelines to systematically define an SHN topology, and increase the rate at which desired decision states in the topology are chosen. Ultimately, we are able to control the rate at which desired decision states activate for input signal-to-noise ratios across six orders of magnitude.
Keywords
bioinspired robotics, low signal-to-noise ratio, mutual inhibition, robot decision making, robotic control, stable heteroclinic channel
Language
English
Publication Title
Bioinspiration and Biomimetics
Grant
2047330
Rights
© 2025 The Author(s). This is an Open Access work distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Natasha A Rouse et al 2025 Bioinspir. Stable Heteroclinic Channels as a Decision-Making Model: Overcoming Low Signal-To-Noise Ratio with Mutual Inhibition. Biomim. 20 036004
Manuscript Version
Final Publisher Version