Introduction

Drooid develops decentralized swarms of bioinspired nano-drones that can access tight spaces inaccessible to humans or larger drones to carry out critical search and rescue missions. Self-coordinating via blockchain technology, these autonomous drones efficiently explore hazardous environments, locate victims, and return key data to the base.

Algorithm 

We introduce the "sensing bug" algorithm, where robots are deployed in the environment and spread out as much as possible, avoiding obstacles and each other, while searching for human vital signs. As long as no drone has sensed any exhaled carbon dioxide from respiration or detected heartbeat/motion sounds, they continue to disperse.

As soon as one drone detects human vital signs, it initiates a gossip-based communication protocol to rapidly share this information through the drone network. Specifically, the detecting drone will randomly select a neighboring drone and pass along the "victim detected" message. Each recipient drone will then, with a certain probability, choose another random neighbor to forward the message to.

This decentralized, epidemic-style propagation allows the information about the victim's location to quickly spread through the entire drone swarm, without the need for any encryption or complex secure communication protocols. The randomized gossip approach ensures resilience, as the message can still reach all drones even if some connectivity is lost.

As the "victim detected" message propagates, the drones in the swarm converge on a collaborative search pattern, using particle swarm optimization to home in on the maximum concentration of carbon dioxide/heartbeat signals. Each drone acts as a "particle" in the optimization, helping to pinpoint the victim's location.  

When the drone battery is less than 50 percent charged or all mission operation is terminated via command control, all of the swarm proceeds to follow a radio beacon signal back to their home base.

Algorithm Design

1. Deployment and Dispersal:

• Let $P_i$ represent the position of drone $i$ in the environment.
• The drones aim to spread out, avoiding obstacles and each other. This can be represented by a dispersal function $f_d$ that minimizes the inter-drone distance and avoids obstacles.

2. Search Condition:

• Define a function $S$ that represents the sensing condition. If no drone has detected human vital signs, they continue to disperse.

3. Collaborative Search Activation:

• Once a drone detects human vital signs, it triggers a gossip-based communication protocol to propagate this information through the swarm.
• Let $C$ be the condition for collaborative search activation, which is triggered when a drone detects human vital signs.

4. Gossip-based Information Propagation:

• When a drone $i$ detects human vital signs, it initiates the gossip protocol by randomly selecting a neighboring drone $j$ and transmitting the "victim detected" message.
• Each recipient drone $j$ will, with a probability $p$, select another random neighbor drone $k$ and forward the message to it.
• This decentralized, epidemic-style propagation continues until the information has reached all drones in the swarm.

5. Particle Swarm Optimization (PSO):

• Once the "victim detected" message has propagated through the swarm, the drones converge on a collaborative search pattern using the Particle Swarm Optimization (PSO) algorithm.
• Each drone is considered a "particle" in the optimization, searching for the maximum concentration of carbon dioxide/heartbeat signals.

6. Return to Home Base:

• If a drone's battery is less than 50% charged or the mission is terminated, the drone will follow a radio beacon signal back to its home base.