Insect-Computer Hybrid System for Autonomous Search and Rescue Mission

TL;DR

This paper introduces the first insect-computer hybrid system designed for autonomous search and rescue, combining living insects with microcontrollers for navigation and human detection in complex, unstructured environments.

Contribution

It presents a novel hybrid system integrating insect navigation and machine learning-based human detection, advancing autonomous rescue technology with low power consumption.

Findings

Successful autonomous navigation in complex terrains

High-accuracy human presence detection using infrared and machine learning

Low power consumption suitable for extended operations

Abstract

There is still a long way to go before artificial mini robots are really used for search and rescue missions in disaster-hit areas due to hindrance in power consumption, computation load of the locomotion, and obstacle-avoidance system. Insect-computer hybrid system, which is the fusion of living insect platform and microcontroller, emerges as an alternative solution. This study demonstrates the first-ever insect-computer hybrid system conceived for search and rescue missions, which is capable of autonomous navigation and human presence detection in an unstructured environment. Customized navigation control algorithm utilizing the insect's intrinsic navigation capability achieved exploration and negotiation of complex terrains. On-board high-accuracy human presence detection using infrared camera was achieved with a custom machine learning model. Low power consumption suggests system suitability for hour-long operations and its potential for realization in real-life missions.