Swarm Robotics
A fleet of compact robots that coordinate as a single distributed system — covering large areas, sharing what they sense and finishing the job faster together than any one machine could alone.
Swarm robotics flips the usual trade-off. Instead of one expensive, complex machine, you deploy many simple, affordable units that talk to each other. The group behaves like a single organism: tasks are divided automatically, coverage is parallelized, and the loss of any one robot barely dents the mission.
Each KD-SWARM agent runs the same on-board autonomy and shares a common map over a low-latency mesh network. Robots negotiate who does what using decentralized algorithms — no central brain to fail. Add more units and the swarm simply gets faster and more thorough; the software scales without rewiring.
The result is graceful degradation and elastic throughput. For a field that needs scouting, a warehouse that needs inventory counts, or a disaster site that needs searching, the swarm spreads out, maps in parallel, and converges on the areas that need attention most.
Decentralized coordination
Robots assign tasks among themselves with consensus algorithms — there's no single point of failure to take down the fleet.
Shared world model
Every agent contributes to one live map over a mesh radio; what one robot sees, the whole swarm knows within seconds.
Elastic scaling
Run two robots or two hundred on the same software. Throughput grows with fleet size; coverage time falls.
Self-healing missions
If a unit drops out, neighbours redistribute its workload automatically and the mission continues.
Formation & area control
Set behaviours — line-sweep, grid-cover, follow-the-leader, encircle — and the swarm self-organizes into them.
Low unit cost
Small, repairable agents keep capital cost down and make redundancy affordable.
| Agent footprint | ≈ 30 × 30 cm per unit |
|---|---|
| Fleet size | 2 – 200+ coordinated agents |
| Mesh network | Sub-GHz + Wi-Fi mesh, self-forming |
| Inter-agent latency | < 50 ms typical |
| Coordination | Decentralized, consensus-based |
| Per-agent runtime | 4–6 hrs, auto-return to charge |
| Localization | UWB anchors + visual odometry |
| Failure tolerance | Graceful — no central controller |
- Large-area agricultural scouting and pollination support
- Warehouse inventory and cycle counting in parallel
- Search-and-cover in disaster and SAR scenarios
- Environmental monitoring across wide outdoor sites
- Collaborative mapping of unknown indoor spaces
Define the area
Outline the zone and the goal — scout, count, search, monitor. The swarm divides the space into sectors automatically.
Disperse
Agents fan out, form the mesh network and begin parallel coverage, each claiming a sector through negotiation.
Share & adapt
Robots pool their observations into one map and re-balance: idle units help finish busy sectors, dropped units are covered.
Converge
The swarm focuses on areas flagged as interesting, then returns to dock. You get one consolidated result, not many disjoint logs.
Interested in the KD-SWARM?
Tell us the terrain, the payload and the job — we'll tell you what it takes.