XPolicyLab Cuts Robot Policy Integration From NM to N Plus M
A shared policy contract and isolated client/server runtime let 42 robot policies connect to simulations and real-robot evaluation without pairwise adapters.
Autonomous systems, robot learning, motion planning, and manipulation.
A shared policy contract and isolated client/server runtime let 42 robot policies connect to simulations and real-robot evaluation without pairwise adapters.
An 8B vision-language model predicts image-space waypoints from a single RGB stream, reaching 77.4% unseen-environment success while cutting supervised training tokens 22×.
Smartphone capture and a modular processing toolchain turn 2,000 hours of human manipulation video into structured supervision for embodied models.
A two-stage VLA recipe combines 100K hours of UMI trajectories with cross-embodiment post-training, reaching 57.4% on RoboCasa365.
Eight sites across five countries and seven robot embodiments add 72.1K verified trajectories for testing navigation and prediction under varied crowds.
Explicit reasoning and pixel-goal anchors decouple cognition from control, raising POI arrival to 77.3% with a reported 35.0% gain.
A Cosmos-derived causal diffusion model uses simulator state, action cues, and a streaming KV cache to render 704×1280 rollouts at 68–105 FPS.
An 8B backbone couples perception, planning, action, and progress estimation, improving 14 of 18 spatial benchmarks over ACE-Brain-0.
A benchmark of VLA models across 18 tasks reveals strong object generalization but weak force control and long-horizon planning.