Stable heteroclinic channels as a decision-making model: overcoming low signal-to-noise ratio with mutual inhibition

被引:0
作者
Rouse, Natasha A. [1 ]
Horchler, Andrew D. [4 ]
Chiel, Hillel J. [2 ,3 ]
Daltorio, Kathryn A. [1 ]
机构
[1] Case Western Reserve Univ, Dept Mech & Aerosp Engn, Cleveland, OH 44106 USA
[2] Case Western Reserve Univ, Dept Biol, Dept Neurosci, Cleveland, OH 44106 USA
[3] Case Western Reserve Univ, Dept Biomed Engn, Cleveland, OH 44106 USA
[4] Astrobotic Technol, Future Missions & Technol Team, Pittsburgh, PA USA
关键词
robotic control; bioinspired robotics; stable heteroclinic channel; robot decision making; mutual inhibition; low signal-to-noise ratio; FINITE-STATE MACHINE; NETWORKS; SYSTEM;
D O I
10.1088/1748-3190/adc057
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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.
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页数:12
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