ArticleNature communications2024
Avian-inspired embodied perception in biohybrid flapping-wing robotics.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- A triboelectric airflow field sensor enables cross-scale multi-parameter sensing in meter-scale flapping-wing aircrafts.Science advances · 2026Article
- Flexible, super-resolution skin with in-sensor hyperdimensional computing for real-time pressure field perception.Science advances · 2026Article
- Ion-electron synergy-enhanced flexible highly sensitive wireless sensing system with wide strain range.Microsystems & nanoengineering · 2026Article
- AI-Enabled Flexible Sensing Skin for Next-Generation Aircraft: Toward Embodied Intelligence.Research (Washington, D.C.) · 2026Review
- Trajectory planning for drone landing, incorporating wind-sensing capabilities, operational and safety objectives, and reinforcement learning.Communications engineering · 2025Article
- Spatially programmable origami networks enable high-density mechanical computing for autonomous robotics.Nature communications · 2025Article
- Dynamically Controlled Flight Altitudes in Robo-Pigeons viaResearch (Washington, D.C.) · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Avian feather intricate adaptable architecture to wing deformations has catalyzed interest in feathered flapping-wing aircraft with high maneuverability, agility, and stealth. Yet, to mimic avian integrated somatic sensation within stringent weight constraints, remains challenging. Here, we propose an avian-inspired embodied perception approach for biohybrid flapping-wing robots. Our feather-piezoelectric mechanoreceptor leverages feather-based vibration structures and flexible piezoelectric materials to refine and augment mechanoreception via coupled oscillator interactions and robust microstructure adhesion. Utilizing convolutional neural networks with the grey wolf optimizer, we develop tactile perception of airflow velocity and wing flapping frequency proprioception. This method also senses pitch angle via airflow direction and detects wing morphology through feather collisions. Our low-weight, accurate perception of flapping-wing robot flight states is validated by motion capture. This investigation constructs a biomechanically integrated embodied perception system in flapping-wing robots, which holds significant promise in reflex-based control of complex flight maneuvers and natural bird flight surveillance.
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