🧾Onboarding Process & Platform Usage

Platform User Journey – Swarm Protocol

The typical user journey on Swarm Protocol would go as follows:

User Connection into Swarm Lab

• User lands on the Swarm Protocol web application or a partner research portal.

• User enters qualification or participation information (researcher, student, developer, or contributor).

• User selects desired experiment type (e.g., drone swarm coordination, warehouse robotics, multi-agent navigation).

• User uploads parameters, models, or datasets (optional).

• Payment is gathered if needed (simulations can be sponsored by the community treasury, research institutions, or self-funded via $SWARM tokens).

Enrollment

• Enrollment request is passed to the Swarm Protocol Orchestration Layer via API.

• Simulation environment is provisioned in the cloud with parameters, runtime, and agent configurations.

• Credentials, experiment IDs, and access endpoints are returned to the user.

• User’s project connects into the distributed simulation lab.

User Successfully Connected to Swarm Lab

• Experiments run in cloud-native environments at scale, eliminating hardware dependency.

• AI-driven models accelerate swarm behaviors (coordination, optimization, resource-sharing).

• Results and performance metrics are logged, visualized, and shared with the user.

• Community voting and funding mechanisms can decide if experiments should be extended, scaled, or implemented into real-world robotic fleets.

Expected Value to User

• Cost to run simulations expected in the $1–50 equivalent range, depending on complexity and scale.

• Value to the user per experiment can be $500–10,000/year, depending on the insights generated, published research, or deployment into production environments.

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Onboarding & Integration

A typical researcher, developer, or robotics company interaction for connecting to the Swarm Protocol Simulation & Integration Service:

• Researchers, developers, or robotics companies identify which simulation protocols, environments, and agent frameworks they need to use (e.g., ROS, Gazebo, Unity, Webots).

• They share the agent types, swarm sizes, models, and any specialized dataset or algorithm requirements.

• Organizations map their use cases (e.g., drone coordination, warehouse logistics, autonomous fleets) to the simulation programs available.

• Their servers, models, or agents connect to the Integration Service using Swarm Protocol APIs.

Integration Steps:

• Test exchange of experiment registry data.

• Test supported protocols, agent behaviors, and environment capabilities.

• Test exchange of experiment IDs, access credentials, and token-gated permissions.

• Robotics companies and researchers integrate the Routing APIs into their own dashboards or research portals, allowing contributors to connect experiments directly.

The Swarm Protocol website will also host a routing page, enabling researchers and contributors to launch experiments without requiring deep integration or branded front-ends.

Swarm Protocol lowers the barrier for running large-scale swarm robotics experiments to a single connection point. With one connection, unlock access to thousands of contributors, shared datasets, and distributed compute capacity.

Create a stable, secure, and unified global simulation environment with Swarm Protocol through a global registry for all swarm agents. A dedicated open-source blockchain layer will be explored to democratize, coordinate, and validate experiments across participants through standardized multi-agent research protocols:

Agent Type	Simulation Standard
Drones & UAVs	ROS 2, PX4, Gazebo
Warehouse Robots	ROS 2, Unity Robotics Hub
Autonomous Vehicles	Apollo, CARLA
General Multi-Agent Systems	PettingZoo, MARLlib

Through a unified, Web3-powered simulation layer, agents, environments, researchers, and contributors will be able to join experiments and validate outcomes through a distributed consensus of validators. This ensures security, transparency, and longevity for experiments that drive the future of swarm robotics.