Sensory feedback control
Sensory feedback control
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Background
Earlier model-based control studies of octopus arm movement typically lack the integration of sensory information into the motor control. How octopuses use their sensing capabilities to control their arms remains an open question.
We propose a novel sensory feedback control law for octopus arms. The control law is inspired by several behavioral observations and biophysical experiments:
Local target bearing sensing through suckers;
Bend propagation;
The arm is passive beyond the bend point.
Sucker sensing
Bend propagation
Muscular arm with sensor model
The arm is actuated by its intricate internal musculature. For simplicity, we consider a planar, inextensible, and unshearable arm. Then, the muscle actuation only requires two longitudinal muscles -- one on the top, and another on the bottom. When these muscles contract, they locally bend the arm.
The sensory information includes the bearing angle $\alpha$ between the target vector $\boldsymbol{\rho}$ and the tangent vector $\mathsf{a}$, and the arc-length $\bar{s}$ of the closest point to the target.
Schematic of the sensorimotor control
Theoretical contribution
Simulation Results
Limitations
This control law can only track a moving target instead of catching it due to the property of asymptotic stability
Presentations
Regular session TuBT11 - Distributed Parameter System II from 2022 Conference on Decision and Control - Cancun, Mexico, Dec. 6-9, 2022.
Publications
T. Wang, U. Halder, E. Gribkova, M. Gazzola, and P.G., Mehta, "A sensory feedback control law for octopus arm movements," in 2022 Conference on Decision and Control (CDC). IEEE, 2022, pp. 1059-1066 .
Acknowledgements
Financial support from ONR MURI N00014-19-1-2373, NSF/USDA #2019-67021-28989, and NSF EFRI C3 SoRo #1830881.
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