Axis Robotics Releases AXIS: A Browser-Based Data Engine With 207 Robot Manipulation Tasks and 50,129 Trajectories
Axis Robotics and academic partners released AXIS, a browser-based teleoperation system yielding 207 manipulation tasks and 50,129 trajectories that lifts pi0.5 to 88.8 on LIBERO-Plus.
A team from Axis Robotics, UC Berkeley, Georgia Tech, and NTU introduced AXIS, a browser-based data engine where contributors teleoperate a simulated Franka Research 3 in a MuJoCo WebAssembly frontend while GPU backends handle task generation, training, and evaluation. The released snapshot holds 207 tasks, 50,129 episodes, and 60K+ task or scene variants from more than 70,000 community contributors. Continual pretraining of pi0.5 on AXIS data raises LIBERO-Plus performance from 83.9 to 88.8, versus 57.5 for a volume-matched RoboCasa365 control; the 2.36 TB dataset is gated for non-commercial academic use.
- Browser teleoperation in MuJoCo-WASM; GPU backend handles task generation and training
- 207 tasks, 50,129 trajectories, 60K+ variants from 70,000+ contributors
- pi0.5 plus AXIS reaches 88.8 on LIBERO-Plus versus 83.9 baseline
- Dataset gated at 2.36 TB, non-commercial academic use; no policy checkpoints
- Organizations
- Axis RoboticsUC BerkeleyGeorgia TechNTU
- AI models
- pi0.5
From the original article
4 min read at marktechpost.com
Robot datasets have grown far slower than the models trained on them, mostly because collection stays locked to lab hardware. AXIS moves demonstration collection into a web browser and pushes everything expensive to backend GPUs. The result is 207 tasks and 50,129 verified Franka trajectories, and continual pretraining that lifts π0.
By Michal Sutter · marktechpost.com
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