Nanorobot Swarm: Communication Range & Task Allocation

Swarm Parameters

Swarm size 90

Communication range 3.0

Response threshold θ 0.50

Motion inertia 0.55

Swarm Telemetry

Network connected

Robots engaged

0 / 0

Tasks completed

Idle / searching

Working task A

Working task B

Working task C

How it works

Each nanorobot senses a task's chemical/optical stimulus directly only within a short range. Beyond that, information about the task must hop robot-to-robot across a communication network — an edge exists between two robots only when their distance is below the communication range R. This is the same 1-hop-adjacency assumption behind Zigbee-style short-range swarm protocols.

edge(i,j) exists  iff  |pᵢ − pⱼ| ≤ R
relayed stimulus:  Sⱼ = max( Sⱼ , Sᵢ · k )   (k = per-hop attenuation, propagated along edges)

Once a robot has (possibly relayed) knowledge of a stimulus level S for some task, it does not commit immediately. Its probability of engaging follows the classic response-threshold model of division of labour in decentralized swarms and social insects:

P(engage | S) = Sⁿ / (Sⁿ + θⁿ)      (n = 2)

A low θ makes robots trigger-happy on weak signals; a high θ means only strongly-corroborated, multi-hop-confirmed tasks recruit workers. Engaged robots steer toward the task and add to its progress bar; when a task completes it relocates and the cycle repeats. The motion inertia slider blends a robot's current heading with its desired heading — low inertia gives twitchy, fast-reacting robots, high inertia gives smooth but sluggish ones.

The network connected readout is the fraction of the swarm in the single largest communication-linked cluster — when it drops, the swarm has fragmented into islands that cannot relay task information to each other, exactly the resilience trade-off decentralized swarms must manage.

Communication link Task beacon

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