Sound Source Localization through 8 MEMS Microphones Array Using a Sand-Scorpion-Inspired Spiking Neural Network.

Area of Science:

• Bioacoustics
• Neuroethology
• Robotics

Background:

• Arachnids like sand-scorpions utilize ground wave sensing for environmental perception.
• They possess remarkable neuronal anatomy enabling detection of atomic-level amplitudes and precise acoustic localization (within 13°).

Purpose of the Study:

• To develop a bio-inspired prototype sound source localization system.
• To emulate the sensory capabilities of arachnids in an artificial system.

Main Methods:

• Custom hardware featuring eight Micro-Electro-Mechanical Systems (MEMS) microphones, analogous to arachnid feet.
• A spiking neural network model for processing acoustic data and localizing sound sources.

Main Results:

• The prototype system demonstrated a reduced localization error compared to natural systems.
• Achieved high accuracy in identifying the origin of acoustic stimuli.

Conclusions:

• Biomimetic approaches can lead to highly effective sound localization technologies.
• This system offers a promising foundation for advanced acoustic sensing and robotic navigation.