Locomotion

Uneven Terrain Locomotion

Uneven terrain locomotion is the problem of legged or wheeled robots traversing ground that is irregular, sloped, discontinuous, or deformable, such as stairs, rubble, trails, and vegetation. Modern legged approaches train reinforcement learning policies over procedurally generated terrains in massively parallel simulation, often with teacher-student distillation from privileged terrain information, as in work on ANYmal, and perceptive variants fuse elevation maps or depth vision with proprioception to place feet deliberately.

Why it matters for physical AI

Terrain robustness is what separates robots confined to flat warehouse floors from those useful in construction, inspection, agriculture, and disaster response, and it remains the benchmark capability for legged platforms.