Why benchmarks matter
Embodied AI spans language understanding, spatial reasoning, perception, manipulation, navigation and long-horizon execution. No single benchmark captures the full stack.
Benchmark families
Spatial reasoning: evaluates whether models understand object positions, geometry and spatial relationships.
Robot manipulation: measures task completion, grasping, placement and interaction.
Embodied question answering: tests answering questions grounded in physical environments.
Navigation: evaluates movement toward goals while respecting environmental constraints.
Long-horizon tasks: tests multi-step execution and recovery from failures.
Cross-embodiment evaluation: examines whether learned behavior transfers between different robot bodies.
Simulation benchmarks: provide repeatable environments for policy comparison and large-scale training.