ArticleFrontiers in neurorobotics2024
Re-framing bio-plausible collision detection: identifying shared meta-properties through strategic prototyping.
Article in Frontiers in neurorobotics, 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.
- Enhanced LGMD Model with Adaptive Probabilistic Regulation for Compound Interference.Biomimetics (Basel, Switzerland) · 2026Article
- Robust Looming Spatial Localization in Dim Light via Daubechies Wavelet-Fused ON/OFF Pathways.Biomimetics (Basel, Switzerland) · 2026Article
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3 authors.
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Abstract
Insects exhibit remarkable abilities in navigating complex natural environments, whether it be evading predators, capturing prey, or seeking out con-specifics, all of which rely on their compact yet reliable neural systems. We explore the field of bio-inspired robotic vision systems, focusing on the locust inspired Lobula Giant Movement Detector (LGMD) models. The existing LGMD models are thoroughly evaluated, identifying their common meta-properties that are essential for their functionality. This article reveals a common framework, characterized by layered structures and computational strategies, which is crucial for enhancing the capability of bio-inspired models for diverse applications. The result of this analysis is the Strategic Prototype, which embodies the identified meta-properties. It represents a modular and more flexible method for developing more responsive and adaptable robotic visual systems. The perspective highlights the potential of the Strategic Prototype: LGMD-Universally Prototype (LGMD-UP), the key to re-framing LGMD models and advancing our understanding and implementation of bio-inspired visual systems in robotics. It might open up more flexible and adaptable avenues for research and practical applications.
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