Bimanual platforms like ALOHA enable two-arm coordinated manipulation — the hardest class of tabletop manipulation tasks. Both arms must move in precise coordination, mirroring human two-handed dexterity.
Use cases we support:
Why teams partner with us:
Bimanual coordination is where most tabletop policies fail.
Our rigs are purpose-built for two-arm demos — not adapted single-arm setups. That difference shows in data quality, sync accuracy, and task success rates.
14 bimanual rigs
30Hz joint logging
<8ms bilateral latency
Production ALOHA variants and dual-cobot configurations across the field.
Stanford
Bench
Mobile
Dual cobot
Research
BYO config
The streams a bimanual VLA or contact-rich policy actually trains on.
Synchronized left and right arm trajectories, joint and end-effector.
Per-arm TCP pose in your robot frame, calibrated per session.
Wrench data from each arm, time-aligned for two-handed contact-rich tasks.
Wrist cameras on both arms plus scene cameras, frame-perfect.
A four-stage integration designed around bilateral teleop latency budgets.
Both arms calibrated together. Bilateral latency measured and locked.
Operators trained on coordination patterns specific to your task.
Trajectories captured with daily QA on coordination quality.
Force sensor and multi-camera streams aligned per session.
Six hardware families. One data partner.
Whole-body trajectories for bipedal robots.
Long-horizon tasks on mobile platforms.
High-throughput arm data for factory settings.
Remote operator-driven data collection.
In-person task demos for imitation learning.
Bounding boxes, segmentation, action labels.
FAQ
Tell us the rig and the coordination pattern. Two-week ramp to first batch.