Central pattern generators evolved for real-time adaptation to rhythmic stimuli

Read:: - [ ] Szorkovszky et al. (2023) - Central pattern generators evolved for real-time adaptation to rhythmic stimuli ➕2024-02-20 !!2 rd citation todoist Print::  ❌ Zotero Link:: Zotero Files:: attachment Reading Note:: Web Rip:: url:: https://dx.doi.org/10.1088/1748-3190/ace017

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Abstract

For a robot to be both autonomous and collaborative requires the ability to adapt its movement to a variety of external stimuli, whether these come from humans or other robots. Typically, legged robots have oscillation periods explicitly defined as a control parameter, limiting the adaptability of walking gaits. Here we demonstrate a virtual quadruped robot employing a bio-inspired central pattern generator (CPG) that can spontaneously synchronize its movement to a range of rhythmic stimuli. Multi-objective evolutionary algorithms were used to optimize the variation of movement speed and direction as a function of the brain stem drive and the centre of mass control respectively. This was followed by optimization of an additional layer of neurons that filters fluctuating inputs. As a result, a range of CPGs were able to adjust their gait pattern and/or frequency to match the input period. We show how this can be used to facilitate coordinated movement despite differences in morphology, as well as to learn new movement patterns.

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Further Reading

• [1] Ijspeert A J 2008 Central pattern generators for locomotion control in animals and robots: a review Neural Netw. 21 642–53 rd p5 ➕2025-02-07

• [2] Aoi S, Manoonpong P, Ambe Y, Matsuno F and Wörgötter F 2017 Adaptive control strategies for interlimb coordination in legged robots: a review Front. Neurorobot. 11 39 rd p5 ➕2025-02-07

• [3] Dasgupta S, Goldschmidt D, Wörgötter F and Manoonpong P 2015 Distributed recurrent neural forward models with synaptic adaptation and CPG-based control for complex behaviors of walking robots Front. Neurorobot. 9 10 rd p5 ➕2025-02-07

• [4] Steingrube S, Timme M, Wörgötter F and Manoonpong P 2010 Self-organized adaptation of a simple neural circuit enables complex robot behaviour Nat. Phys. 6 224–30 rd p5 ➕2025-02-07

Extracted Annotations and Comments

Page 1

Biologically inspired central pattern generators (CPGs) are useful for their properties, typical of self-organized systems, such as distributed control and robustness to perturbations [1, 2]. This allows adaptive behaviours such as compensation for physical damage [3] or walking in novel environments [4]. Spontaneous entrainment of motion patterns to sensory input is also expected from such systems, and adaptation of bio-inspired CPGs to body and environmental mechanics has indeed been widely demonstrated [5–8].