CLARU
Gwanwoo2026mit

OGBench mirror: antmaze-large-navigate-v0

Unofficial mirror of the antmaze-large-navigate-v0 dataset from OGBench, a benchmark for offline goal-conditioned reinforcement learning. The dataset consists of simulated ant navigation trajectories in a large maze environment.

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Why This Matters for Physical AI

OGBench provides a standardized offline goal-conditioned RL benchmark for evaluating algorithms that learn from pre-collected robot trajectories without online environment interaction, relevant for developing practical robotic learning methods.

Technical Profile

Modalities
proprioception
Robot Embodiments
ant
Action Space
joint_velocities
Environment
simulation
Task Types
navigationgoal-conditioned
Data Format
npz
Annotation Types
goal_labels
License
mit
Part of the OGBench family

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