ArticleThe European physical journal. E, Soft matter2024
Reinforcement learning of biomimetic navigation: a model problem for sperm chemotaxis.
Article in The European physical journal. E, Soft matter, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Embodied Cross-Domain Intelligence in Biomedical Microrobots: A Review.Cyborg and bionic systems (Washington, D.C.) · 2026Review
- Chemotactic navigation in robotic swimmers via reset-free hierarchical reinforcement learning.Nature communications · 2025Article
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2 authors.
Funding
Abstract
Motile biological cells can respond to local environmental cues and exhibit various navigation strategies to search for specific targets. These navigation strategies usually involve tuning of key biophysical parameters of the cells, such that the cells can modulate their trajectories to move in response to the detected signals. Here we introduce a reinforcement learning approach to modulate key biophysical parameters and realize navigation strategies reminiscent to those developed by biological cells. We present this approach using sperm chemotaxis toward an egg as a paradigm. By modulating the trajectory curvature of a sperm cell model, the navigation strategies informed by reinforcement learning are capable to resemble sperm chemotaxis observed in experiments. This approach provides an alternative method to capture biologically relevant navigation strategies, which may inform the necessary parameter modulations required for obtaining specific navigation strategies and guide the design of biomimetic micro-robotics.
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