Article
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Preserved in Portico This version is not peer-reviewed
Neural Simulation of Actions for Serpentine Robots
Version 1
: Received: 22 June 2024 / Approved: 22 June 2024 / Online: 24 June 2024 (08:15:33 CEST)
A peer-reviewed article of this Preprint also exists.
Morasso, P. Neural Simulation of Actions for Serpentine Robots. Biomimetics 2024, 9, 416, doi:10.3390/biomimetics9070416. Morasso, P. Neural Simulation of Actions for Serpentine Robots. Biomimetics 2024, 9, 416, doi:10.3390/biomimetics9070416.
Abstract
Neural or mental simulation of actions is a powerful tool for allowing cognitive agents to develop Prospection Capabilities that are crucial for learning and memorizing key aspects for challenging skills. In previous studies we developed an approach based on the animation of the redundant human Body Schema based on the Passive Motion Paradigm (PMP). In this paper we show that this approach can be easily extended to hyper-redundant serpentine robots as well as to hybrid configurations where the serpentine robot is functionally integrated with a traditional skeletal infrastructure. A simulation model is analyzed in detail showing that it incorporates spatio-temporal features discovered in the biomechanical studies of biological hydrostats like the elephant trunk or the octopus tentacles. It is proposed that such generative internal model can be the basis for a cognitive architecture appropriate for serpentine robots, independent of the underlying design and control technologies. Although robotic hydrostats have received a lot of attention in the last decades, the great majority of research activities have been focused on the actuation/sensorial/material technologies that can support the design of hyperredundant soft robots as well as the related control methodologies. The cognitive level of analysis has been limited to motion planning, without addressing synergy formation and metal time travel. This is where the contribution of the paper is focused on.
Keywords
Cognitive robotics; Biomimetic robotics; Hydrostat; Neural simulation of action; Prospection; Passive Motion Paradigm; Generative Body Schema; Degrees of freedom problem
Subject
Biology and Life Sciences, Neuroscience and Neurology
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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