A Polychromatic Neuromorphic Visual System Inspired by Biomimetics for Miniature Insect Robots

Area of Science:

• Neuromorphic engineering
• Organic electronics
• Bio-inspired robotics

Background:

• The demand for intelligent systems with enhanced human-machine interaction and robotic capabilities necessitates advancements in neuromorphic environmental information encoding, synaptic signal processing, and motion control.
• Current systems often lack the efficiency and adaptability of biological visual systems.

Purpose of the Study:

• To develop a bio-inspired system replicating human visual perception and synaptic functions for advanced robotic applications.
• To create efficient and adaptable neuromorphic electronic components for intelligent machines.

Main Methods:

• Utilized bulk heterojunction organic photosynapses (BHJ-OPS) with a two-terminal architecture.
• Investigated ultra-broadband photodetection (365-1060 nm) and low energy consumption (0.2 fJ/synaptic event) for near-infrared (NIR) perception.
• Integrated photovoltaic effects with electron trapping to achieve bio-synaptic characteristics like memory and learning.
• Implemented a 26 × 26 memristor network for miniature insect robot control.

Main Results:

• BHJ-OPS demonstrated ultra-broadband photodetection and record-low energy consumption for NIR perception.
• The organic photosynapses exhibited short-term memory, long-term memory, and experiential learning capabilities.
• A synapse array endowed with multispectral color-discrimination was developed.
• Miniature insect robots capable of night-time foraging and predator evasion were successfully implemented.

Conclusions:

• The developed BHJ-OPS show significant potential for creating miniature insect robots with self-regulation and adaptability.
• This technology advances the development of intelligent robots for exploration, monitoring, and rescue missions.
• The study highlights the efficacy of bio-inspired neuromorphic systems in bridging biological and artificial intelligence.