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Platform 03

Mobile manipulation platforms

Capture data on mobile platforms that combine navigation, manipulation, and long-horizon task chaining.

8
Mobile platforms supported
30 min
Avg episode length
5K+
Trajectories collected
MOBILE MANIPULATOROBJnav pathNAV + ODOMETRYARM JOINT DATAEPISODE TIMELINE30-MINUTE EPISODE TIMELINENAVIGATEPICKPLACE0:0010:0020:0030:0030 minavg episode length5K+trajectories collected5platforms supportedDomains:Household • Retail restocking • Hospital logistics • Office delivery

What is a mobile manipulation platform?

Mobile manipulators combine navigation and arm control into long-horizon episodes — the most demanding collection format in robotics. A single 30-minute demo integrates dozens of sub-tasks across a real environment.

Use cases we support:

  • Household tasks — multi-room pick-and-place, loading appliances, surface cleaning
  • Retail restocking — shelf manipulation, inventory handling in live environments
  • Hospital logistics — cart transport, supply delivery, contactless interaction
  • Office delivery — door navigation, handover, multi-floor routing

Why teams partner with us:

  • 5 mobile manipulation platforms supported
  • Specialist 30-minute episode operators — stamina and consistency trained
  • 5,000+ trajectories collected across real-world environments
  • Episode QA at the sub-task level, not just end-state verification

Long episodes demand operator stamina and consistent quality.

Our team trains specifically for 30-minute uninterrupted demos — the operator fatigue that degrades data quality in long episodes is a collection discipline problem, not just a platform problem.


30 min avg episode length
5K+ trajectories collected
5 platforms supported

Models we support

Mobile manipulators across the field

Research workhorses, quadrupeds, and production deployments.

Stretch RE-3

Hello Robot

Fetch

Research

PR2

Legacy

Spot

Boston Dynamics

Aloha Mobile

Bimanual + mobile

Tiago

PAL Robotics

What we capture

What we capture on mobile platforms

Data that captures the chains between navigation and manipulation — the part that breaks policies.

Long-horizon trajectories

Multi-step task captures, 5–30 minutes per episode, with goal annotations.

Nav + manip fusion

Combined movement and contact logs in a single timeline, your fusion stack ready.

Environment maps

Per-episode occupancy and semantic maps for retraining or replay.

Failure recovery

Operator recovery from mid-task failure, labeled for imitation or RL.

How we integrate

From platform bring-up to long-horizon set

A pipeline designed for real environments, not lab benchtops.

1Step 1

Platform bring-up

Robot calibration plus driver bring-up in our pod or your environment.

2Step 2

SLAM verification

Localization and map quality verified before production capture starts.

3Step 3

Long-horizon collection

Multi-step task captures with operator decision points logged.

4Step 4

Failure capture

Targeted re-capture of failure modes from your production model logs.

What our partners say
Long-horizon episodes on Stretch were the gap in our dataset. Roborax ran a thousand episodes in real kitchens in four weeks.
Camille Dubois
Policy Lead, Cohere Robotics

FAQ

Questions about mobile manipulation data

We capture both modalities in a single session — the operator controls navigation and manipulation as a unified task, not in separate passes. This produces the temporally coherent data mobile manipulation policies need.
Kitchens, warehouses, hospitals, retail environments, and purpose-built replicas. We can construct scene replicas at our delivery centers or capture in your actual deployment environment.
As full-episode recordings with synchronized navigation state, manipulation state, and sensor streams. Episodes are segmented by sub-task and delivered with a structured manifest for easy curriculum design.

Scope a mobile program

Tell us the platform, the environment, and the task length. Four weeks to first long-horizon batch.