/ COMPARISONS
Pick the right tool, with the trade-offs on the table.
Every comparison here settles one decision a robot data team actually has to make — the criteria that matter, the failure modes nobody mentions, and a straight recommendation.
/ Strategy
In-House vs Outsourced Robot Data
Building your own operator team versus contracting a data-collection partner trades fixed cost for speed. Here is what you are actually buying either way.
Build vs Buy Robot Data Infrastructure
Robot data infrastructure is more than a recorder — transport, sync, storage, QA, and versioning each cost real time. Here is how to decide who builds it.
Synthetic vs Real Robot Data
Simulation and real teleoperated data solve different parts of manipulation learning. Here is what each is good at, and when a program needs both.
/ Data formats
MCAP vs ROS 2 bag
MCAP and the sqlite3 ROS 2 bag format solve the same problem differently. Here is how they compare on indexing, seek speed, portability, and long-term storage.
LeRobot vs RLDS
LeRobot's parquet-plus-MP4 layout and RLDS's TFRecord episodes-of-steps solve dataset standardization differently. Here is how to pick between them.
HDF5 vs Parquet for Robot Data
HDF5's chunked arrays and Parquet's columnar tables both show up in robot datasets. Here is what each does well, and why most pipelines end up using both.
/ Collection method
VR vs Leader-Follower Teleoperation
VR controllers with retargeting and kinematically matched leader arms are the two dominant teleoperation interfaces — how they differ, and which to pick.
Teleoperation vs Kinesthetic Teaching
Guiding a robot by hand and operating it remotely both produce demonstrations, but the data — and what a policy can learn from it — differs sharply.
Crowdsourced vs Expert Demonstrations
Crowd operators are cheap and diverse; experts are consistent but scarce. Here is how demonstration quality actually affects a trained policy.
Put this into practice.
Tell us what your robots need to learn. We will scope the rig, the operators, the protocol, and the first datasets — usually in one call.