Fiund / How it works
A clear brief. A defined review. A useful handoff.
Robotics data can mean human demonstrations, robot trajectories, observations paired with actions, or recordings of interactions with objects and environments. These are related but not interchangeable. Robotic Datasets helps Fiund buyers specify which signals their training or evaluation project actually requires.
Project workflow
Six stages to discuss with Fiund.
Define the target
Robotics data can mean human demonstrations, robot trajectories, observations paired with actions, or recordings of interactions with objects and environments. These are related but not interchangeable. Robotic Datasets helps Fiund buyers specify which signals their training or evaluation project actually requires.
Write the specification
Task and target embodiment; Required observation and action signals; Episode counts and success criteria; Sensor timing and annotation requirements; Source permissions and intended use. These details establish the project’s review criteria and reveal where further clarification is needed.
Review sourcing fit
Discuss which existing sources or collection approaches could address the brief. Identify access constraints, source documentation, and unanswered permission questions before treating a category as usable inventory.
Inspect representative material
Where appropriate material can be shared, agree on handling and inspect it against the specification. Record defects, coverage gaps, and annotation questions against exact source identifiers.
Agree the project scope
Confirm the selected material, intended uses, preparation work, acceptance criteria, commercial terms, and delivery arrangements in a project-specific agreement.
Review the handoff
Check file references, manifests, documented processing, and accepted exceptions. Keep permission review and technical acceptance explicit, and resolve open issues before the collection is treated as approved for the intended use.
Category decisions
Build the right starting brief.
Embodiment
Robot platform, end effector, controller, camera arrangement, and any compatibility constraints.
Signals
Required observations, state variables, action representation, units, coordinate frames, and timestamps.
Episodes
Task instructions, starts and stops, resets, success labels, and failed or partial attempts.
Transfer conditions
Object variation, environment changes, operator variation, and intended deployment differences.
Common questions
Before you source.
Is ordinary task video a robot trajectory dataset?
No. Video does not inherently contain robot state, joint values, end-effector commands, or control actions. If you require those signals, name them explicitly so sourcing can be evaluated against the right specification.
Can I inquire about a specific robot platform?
Yes. Include the platform, controller, sensors, action representation, and example schema. Availability and collection feasibility must be discussed before any platform-specific data is promised.
Should failed demonstrations be excluded?
That depends on your task. State whether you need successful demonstrations only, recoveries, negative examples, or a labeled mixture, and define how an outcome is judged.